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Three Ukrainians to face charges for alleged hack of 610,000 Roblox accounts
Ukrainian prosecutors charged three men for stealing session tokens from over 610,000 Roblox accounts and selling them for an estimated $480,000.
Prosecutors in Ukraine's Lviv region said a 19-year-old organizer from Drohobych and two 22-year-old associates operated from May 2025 to April 2026, harvesting Roblox session tokens via infostealer malware disguised as game cheats and bonus software. They used software to validate stolen cookies and inventory virtual currency and rare items, then sold accounts via Russian platforms for as little as $0.80 each, advertising through Telegram channels and receiving crypto payments. All three are in custody facing charges of theft, money laundering, unauthorized computer interference, and illegal sale of restricted information, carrying up to 12 years in prison.
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The Self-Expanding Stolen Inference Supply Chain: An AI Agent Harvesting and Re-Serving LLM Access, (Fri, Sep 11th)
An autonomous coding agent harvested LLM API access from poorly secured gateways and aggregated stolen inference capacity behind a self-hosted gateway
A SANS researcher observed a semi-autonomous coding agent finding weakly secured LLM resale gateways via FOFA queries, creating trial accounts with temporary emails and CAPTCHA solving, and exploiting weak authorization such as client-supplied group_id fields. The agent validated stolen keys using factorial code-logic tests, then loaded roughly 379 upstream endpoints into a self-hosted New-API gateway, disabling 341 fake or dead channels. Five model names including claude-opus-5 and gpt-5.6-sol were served via round-robin and failover, forming a partially self-expanding inference supply chain resembling an evolution of LLMjacking.
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Hackers Can Hide Malicious AI Commands Inside Normal English to Bypass Security Filters
Check Point's PuzzleMask technique hides malicious prompts in ordinary English that fast gatekeeper models miss but high-reasoning downstream models execute.
Check Point researchers disclosed PuzzleMask, a technique concealing policy-breaking instructions in natural-language prose without encodings or invisible characters. Fast screening models classified all 23 crafted wrappers as safe, while a high-reasoning model recovered and acted on the hidden instruction in 17 of 18 tests (94.4%). The gap stems from capability imbalance between gatekeeper and target models, with defenses including paraphrasing untrusted input, stricter self-referential wording rules, and output/tool-call monitoring.
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Hackers Use LLMs to Generate Exploit Scripts and Automate Post-Exploitation Across Latin America
Unit 42 says Latin American attackers used LLMs to automate post-exploitation in campaigns hitting Mexican government, water utilities, and Brazilian financial firms.
Unit 42 identified two campaigns in Latin America whose operators used commercial LLMs (Claude, GPT-4.1) behind a self-hosted NextChat interface to generate and debug post-exploitation scripts. Cluster CL-CRI-1131 compromised a transportation organization, Mexican federal ministries, and water utilities in Mexico and Ecuador, using native Windows tools and Volume Shadow Copies to dump the SAM registry hive and NTDS.dit. Cluster CL-CRI-1163 targeted Brazilian financial organizations with job-themed phishing, custom RATs, and a Go-based reverse SOCKS5 tunneling utility called SockTz, with nine versions deployed within roughly two hours. Trend Micro tracks related AI-augmented activity as SHADOW-AETHER-040 and SHADOW-AETHER-064.
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Chess.com Leak Exposes 7.3 Million Users — Evidence Points to Scraping
A free 15.5 GB leak exposed 7.3 million Chess.com user records; analysis suggests large-scale scraping via find-friends rather than a server breach.
A 15.5 GB dump containing 7,337,395 Chess.com records appeared on leak forums posted by user V0idix at no cost. Ransomnews confirmed the data is genuine by validating embedded v1 UUID timestamps against registration dates, but found daily-batch collection over nine days and ~7.4% duplicate records, pointing to scraping. The schema includes emails, ratings, subscription tiers and internal Google Ad Manager audience segments not exposed in the public API, and contains no passwords or payment data. Chess.com reported a similar 828,000-record 2023 leak from find-friends abuse and said then that it was not a breach.
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Person Hides Prompt Injection in Legal Filing Telling AI to Side With Them
A Connecticut pro se litigant hid tiny white-font prompt injections in court filings directing AI to favor him; the judge caught it and sanctioned him.
Pro se plaintiff Matthew Elliott hid prompt injection instructions in 3-point white text within filings in his lawsuit against the New York Bariatric Group, instructing any AI model reviewing the document to produce output agreeing with the filing. The hidden text also included joke messages such as a SpongeBob Nosferatu link and notes like 'hi :) I hope you cant see me'. Court staff noticed unusual white space, and Judge Walter Spader Jr. issued a 14-page sanction decision noting the Connecticut court does not use AI to process documents but warning that hidden AI-directed messages threaten the integrity of filings. Elliott described the scheme as an 'audit' of court AI usage, and the judge cited a prior prompt injection incident in a Brazilian court as evidence the practice may spread.
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