#mac

Spanish speakers beware! A new campaign using the Agent Tesla RAT targets Spanish-speaking individuals. Learn how to protect…

It has been discovered that request handling in Extbase can be vulnerable to insecure deserialization. User submitted payload has to be signed with a corresponding HMAC-SHA1 using the sensitive TYPO3 encryptionKey as secret - invalid or unsigned payload is not deserialized. However, since sensitive information could have been leaked by accident (e.g. in repositories or in commonly known and unprotected backup files), there is the possibility that attackers know the private encryptionKey and are able to calculate the required HMAC-SHA1 to allow a malicious payload to be deserialized. Requirements for successfully exploiting this vulnerability (all of the following): - rendering at least one Extbase plugin in the frontend - encryptionKey has been leaked (from LocalConfiguration.php or corresponding .env file)

After weeks of withering criticism and exposed security flaws, Microsoft has vastly scaled back its ambitions for Recall, its AI-enabled silent recording feature, and added new privacy features.

Cybersecurity researchers have disclosed that the LightSpy spyware allegedly targeting Apple iOS users is in fact a previously undocumented macOS variant of the implant. The findings come from both Huntress Labs and ThreatFabric, which separately analyzed the artifacts associated with the cross-platform malware framework that likely possesses capabilities to infect Android, iOS, Windows, macOS,

A security vulnerability in Ariane Allegro Hotel Check-In Kiosks exposed guest data and potentially compromised room access. However,…

A new discovery that the AI-enabled feature’s historical data can be accessed even by hackers without administrator privileges only contributes to the growing sense that the feature is a “dumpster fire.”

### Impact All users are impacted. The zsa application transfers the parse error stack from the server to the client in production build mode. This can potentially reveal sensitive information about the server environment, such as the machine username and directory paths. An attacker could exploit this vulnerability to gain unauthorized access to sensitive server information. This information could be used to plan further attacks or gain a deeper understanding of the server infrastructure. ### Patches Yes, this has been pathed on `0.3.3` ### Workarounds No way to fix other than the patch.

A vulnerability in mlflow/mlflow version 8.2.1 allows for remote code execution due to improper neutralization of special elements used in an OS command ('Command Injection') within the `mlflow.data.http_dataset_source.py` module. Specifically, when loading a dataset from a source URL with an HTTP scheme, the filename extracted from the `Content-Disposition` header or the URL path is used to generate the final file path without proper sanitization. This flaw enables an attacker to control the file path fully by utilizing path traversal or absolute path techniques, such as '../../tmp/poc.txt' or '/tmp/poc.txt', leading to arbitrary file write. Exploiting this vulnerability could allow a malicious user to execute commands on the vulnerable machine, potentially gaining access to data and model information. The issue is fixed in version 2.9.0.

### Summary Jupyter Server on Windows has a vulnerability that lets unauthenticated attackers leak the NTLMv2 password hash of the Windows user running the Jupyter server. An attacker can crack this password to gain access to the Windows machine hosting the Jupyter server, or access other network-accessible machines or 3rd party services using that credential. Or an attacker perform an NTLM relay attack without cracking the credential to gain access to other network-accessible machines.

The number of alleged hacks targeting the customers of cloud storage firm Snowflake appears to be snowballing into one of the biggest data breaches of all time.