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TLD Tracker: Exploring Newly Released Top

Unit 42 tracked 19 newly released top-level domains and found large-scale phishing, unwanted program distribution, and cybersquatting tied to TLD launch dates.

Researchers analyzed 19 new generic TLDs, including .zip, .bot, .ing, and .meme, released or approaching general availability over roughly 18 months. Data from passive DNS, registry zone files, newly registered domain feeds, and the Tranco top-1M list showed phishing campaigns, potentially unwanted program distribution, and domain squatting on these TLDs. Abuse correlated with each TLD's rollout phases, indicating attackers monitor general availability dates to register and weaponize domains. The IANA root database now lists over 1,000 generic TLDs.

Palo Alto Unit 42 · Aug 17, 2026Research

Automobile Camouflage to Hide from Flock Cameras

Schneier on Security highlights a printed vehicle-camouflage pattern tested to defeat Flock surveillance cameras and Axon body cameras.

The post discusses covering cars with printed patterns designed to fool Flock automated license-plate recognition software, with testing reportedly done against Flock and Axon body cameras. Reader comments question effectiveness against other ALPR vendors, Flock's RF MAC-address upgrade, and whether such camouflage might become regulated. The page also contains off-topic comment threads about anti-bot over-blocking and privacy.

Schneier on Security · 9d agoResearch

Mapping out your unknown: A threat hunter’s guide to GitHub

Datadog Security Labs publishes a threat-hunting guide with audit-log queries to detect GitHub token theft, device code phishing, and source code exfiltration.

Datadog's threat-hunting guide covers GitHub audit log queries for detecting compromised accounts, stolen personal access tokens, and malicious OAuth app authorizations. Attackers typically obtain credentials through phishing, credential stuffing, leaked secrets, or device code phishing, then map private repositories, exfiltrate source code, and pivot into connected cloud and CI/CD environments. The guide maps detections to MITRE techniques like T1078 and T1528 and documents GitHub logging quirks affecting attribution, token metadata, and visibility fields.

Datadog Security Labs · 1d agoResearch in the wild1

HYDRA: Quantifying Botnet Resource Thresholds for Efficient Link-Flooding Attacks on LEO Satellite Networks

HYDRA models link-flooding attacks on LEO satellite constellations as botnet minimization, matching prior disruption with 34% fewer bots and 23% less traffic.

HYDRA formulates link-flooding attack variants against LEO constellations such as Starlink and Kuiper as botnet minimization problems, quantifying the smallest bot subset and traffic allocation needed to disrupt communications between targeted geographic areas. Under matched stealth constraints it matches the ICARUS attack's disruption using 34% fewer bots and 23% less aggregate traffic, sustaining over 97% attack success as topology evolves. The framework also evaluates five mitigations, including routing diversification, ingress policing, distance-based constraints, source throttling, and botnet attrition.

arXiv cs.CR · 2d agoResearch

Risky Bulletin: Academics find source code overlaps between Geedge and China's Great Firewall

Academics linked Chinese vendor Geedge Networks' Tiangou Secure Gateway source code to one of the Great Firewall's three traffic filtering capabilities.

US researchers presenting at USENIX Security reconstructed Geedge Networks' Tiangou Secure Gateway firmware from over 100,000 leaked files, including Git repositories with commit history, and matched its filtering behavior to sections of China's Great Firewall. They found only 1 of 3 characterized DNS injectors matched Geedge code, noted the system relies on memory-unsafe C components and copied third-party code, and said its bugs could aid future circumvention tools. Geedge also exports censorship tools to Kazakhstan, Ethiopia, Pakistan, and Myanmar. The newsletter additionally rounds up multiple breaches.

Risky Business News · 27d agoResearch2

terms.txt: A Consent and Compensation Protocol for Agentic Web Access

terms.txt specifies a robots.txt-style protocol for per-path, per-purpose AI crawler consent and compensation, with enforcement adding 0.20-0.65 ms per request.

The paper documents that automated clients now make up most web requests, that training dominates Cloudflare-classified crawling, and that the largest AI platforms fetch thousands of pages per returned visitor while robots.txt cannot express identity, purpose, terms, or price. It specifies terms.txt plus an origin-enforced exchange using Web Bot Auth signatures, signed intent, delegation tokens, HTTP 402 negotiation, and signed receipts. A dependency-free implementation adds 0.20 to 0.65 ms per request on one vCPU.

arXiv cs.CR · 7d agoResearch1