Original release date: January 20, 2023Cisco released a security advisory for a vulnerability affecting Cisco Unified Communications Manager (Unified CM) and Cisco Unified Communications Manager Session Management Edition (Unified CM SME). A remote att…
Original release date: January 19, 2023CISA released one Industrial Control Systems (ICS) advisory on January 19, 2023. This advisory provides timely information about current security issues, vulnerabilities, and exploits surrounding ICS.
CISA encour…
Original release date: January 18, 2023Mozilla has released security updates to address vulnerabilities in Firefox ESR and Firefox. An attacker could exploit some of these vulnerabilities to take control of an affected system.
CISA encourages users an…
Original release date: January 17, 2023CISA has added one new vulnerability to its Known Exploited Vulnerabilities Catalog, based on evidence of active exploitation. This type of vulnerability is a frequent attack vector for malicious cyber actors and …
Original release date: January 17, 2023Today, CISA updated Best Practices for MITRE ATT&CK® Mapping. The MITRE ATT&CK® framework is a lens through which network defenders can analyze adversary behavior and, as CISA Executive Assistant Director …
Original release date: January 17, 2023Today, CISA updated Best Practices for MITRE ATT&CK® Mapping. The MITRE ATT&CK® framework is a lens through which network defenders can analyze adversary behavior and, as CISA Executive Assistant Director …
Original release date: January 17, 2023CISA released four Industrial Control Systems (ICS) advisories on January 17, 2023. These advisories provide timely information about current security issues, vulnerabilities, and exploits surrounding ICS.
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No details, though:
According to the complaint against him, Al-Azhari allegedly visited a dark web site that hosts “unofficial propaganda and photographs related to ISIS” multiple times on May 14, 2019. In virtue of being a dark web site—that is, one hosted on the Tor anonymity network—it should have been difficult for the site owner’s or a third party to determine the real IP address of any of the site’s visitors.
Yet, that’s exactly what the FBI did. It found Al-Azhari allegedly visited the site from an IP address associated with Al-Azhari’s grandmother’s house in Riverside, California. The FBI also found what specific pages Al-Azhari visited, including a section on donating Bitcoin; another focused on military operations conducted by ISIS fighters in Iraq, Syria, and Nigeria; and another page that provided links to material from ISIS’s media arm. Without the FBI deploying some form of surveillance technique, or Al-Azhari using another method to visit the site which exposed their IP address, this should not have been possible…
Cellebrite is an cyberweapons arms manufacturer that sells smartphone forensic software to governments around the world. MSAB is a Swedish company that does the same thing. Someone has released software and documentation from both companies.
With the release of ChatGPT, I’ve read many random articles about this or that threat from the technology. This paper is a good survey of the field: what the threats are, how we might detect machine-generated text, directions for future research. It’s a solid grounding amongst all of the hype.
Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods
Abstract: Advances in natural language generation (NLG) have resulted in machine generated text that is increasingly difficult to distinguish from human authored text. Powerful open-source models are freely available, and user-friendly tools democratizing access to generative models are proliferating. The great potential of state-of-the-art NLG systems is tempered by the multitude of avenues for abuse. Detection of machine generated text is a key countermeasure for reducing abuse of NLG models, with significant technical challenges and numerous open problems. We provide a survey that includes both 1) an extensive analysis of threat models posed by contemporary NLG systems, and 2) the most complete review of machine generated text detection methods to date. This survey places machine generated text within its cybersecurity and social context, and provides strong guidance for future work addressing the most critical threat models, and ensuring detection systems themselves demonstrate trustworthiness through fairness, robustness, and accountability…