30
30
Forgery of C2PA on a Pixel 10
Researcher forged a Google Pixel 10 C2PA content credential with genuine signatures, showing root-level attackers can fake photo provenance.
A Hacker Factor blog post demonstrates an AI-generated 'unicorn glitter milk' news photo carrying a valid, cryptographically signed C2PA manifest traceable to Google's Pixel camera certificate chain, passing validation in Adobe Inspect and the CAI Verify tool with a verified timestamp. The author, working with UMBC's PASAWG working group, reported to Google and C2PA in November 2025 that root access on a Pixel device could sign arbitrary images as camera captures; after 90 days without resolution, details were published. The finding undermines C2PA Assurance Level 2 claims made for Pixel 10 Content Credentials.
38
30
30
30
30
30
30
30
30
30
30
30
30
Re: Retrospective by 'gpg.fail' authors
GPG exploitation talk author clarifies a format-string 0day enabling code execution via printf %n writes and a polyglot PEM certificate payload.
Lexi Groves, author of the gpg.fail talk, clarified on oss-security that the first finding was an actual zero-day: a classic printf injection using %n for memory writes, with multiple X.509 certificates in one PEM file to re-enter and defeat ASLR before calling execv@plt. The payload executed the certificate itself, a polyglot file made by inserting a shebang and bash command into the PEM. A second finding was hash-collided by another party before the author could exploit it.
18
Hacking Public Wi-Fi DNS to Steal Credentials
Attackers can hijack public Wi-Fi DNS to redirect users to credential-stealing fake login pages; commenters debate HTTPS limits and mitigations like encrypted DNS.
The discussion examines how an attacker controlling DNS on shared or public Wi-Fi networks can redirect requests for legitimate services to attacker-controlled servers to steal credentials. Commenters analyze whether HTTPS and certificates mitigate the attack, noting attackers often rely on HTTP or browser trust quirks. Suggested defenses include encrypted DNS (DoH), DNSSEC, and travel routers running OpenWRT. No specific campaign, victims, or indicators are provided.
22
30
30
Automatically Detecting DNS Hijacking in Passive DNS
Unit 42's machine learning pipeline detected 6,729 DNS hijacking events between March and September 2024, hitting political parties, ISPs, and universities.
Unit 42 processes roughly 167 million new DNS records daily and applies a machine learning model using 74 features over 169 TB of passive DNS and geolocation data to flag hijacked domains. From March to September 2024 the pipeline screened over 29 billion records and classified 6,729 as DNS hijacking, averaging 38 detections per day; a new model detects hijacks in customer traffic within about 10 minutes. Notable cases include a Hungarian political party's hijacked domain, defacement of a large utility company and ISP, and university and research center domains repurposed for illicit gambling. DNS hijacking typically relies on stolen registrar or DNS provider credentials or cache poisoning, enabling MitM attacks, phishing, drive-by downloads, and scams.
45
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30