Search: “secrets-scanning”

New AI Attack Hides Malicious Instructions in Normal-Looking Text to Evade Safety Filters

Check Point researchers show crafted prose hides policy-violating instructions that bypass all tested LLM gatekeepers, including GPT-4o mini and Llama Guard 3.

A new prompt-crafting technique embeds malicious payloads inside grammatical, natural-looking text without Base64, invisible Unicode, or obvious encodings, defeating lightweight pre-screening gatekeepers. In testing, all four evaluated gatekeeper models—gpt-4o-mini-2024-07-18, gpt-oss-safeguard:20b, claude-3-haiku-20240307, and llama-guard3:8b—classified the crafted wrappers as safe at a 100% bypass rate across 23 obfuscated prompts. GPT-5 Thinking in high-reasoning mode recovered and acted on the hidden instruction in 17 of 18 tests (~94.4%), often spending over a minute and multiple Python executions. Researchers recommend paraphrasing untrusted input, hardening gatekeeper policies, and applying defense-in-depth controls for agentic deployments.

GBHackers·Sep 11, 05:53 UTC · 5d agoAI safety & security 2 sources

Hackers Disguise CHOSEN BRICK Malware as AI Apps, Antivirus Software and MRI Results

NCSC, FBI, and AIVD warn Iranian state-linked actors deliver CHOSEN BRICK Windows spyware via fake AI apps, antivirus installers, and MRI-result lures.

A joint advisory from the UK NCSC, FBI, and Dutch AIVD details CHOSEN BRICK (FBI tracking name: HEAVYGRAM), Iranian state-linked Windows spyware targeting dissidents, activists, and journalists worldwide since at least 2025. Lures impersonate Pictory, RunwayML, Norton Antivirus, Telegram, Adobe Flash Player, and KeePass, and operators pivot conversations from corporate to personal devices to bypass enterprise controls. The spyware persists via Registry Run keys, adds Microsoft Defender exclusions, uses per-victim Telegram bots for command-and-control, and exfiltrates screenshots, audio, email, and chat data via Telegram and cloud services, with some victim data appearing on pro-Iranian leak sites.

GBHackers·updated 12:00 UTC · 2h ago·first 06:57 UTC · 7h agoMalware in the wild 5 sources

Rare Not Random Using Token Efficiency for Secrets Scanning

Researcher proposes token efficiency (string length divided by BPE token count) as a better post-regex filter than entropy for secrets scanning, validated on CredData.

The post explores whether Byte-Pair Encoding tokenization can replace Shannon entropy as the primary filter for candidate secrets captured by regex in tools like Gitleaks. It defines 'token efficiency' as string length divided by token count under the cl100k_base tokenizer; secret-like strings such as GitHub tokens tokenize into many small tokens and score low, while natural text scores high. Evaluating labeled secrets from the CredData dataset shows a usable separation, with roughly 2.5 suggested as a minimum cutoff versus Gitleaks' 3.5 entropy threshold. The technique is positioned as a post-regex filtering step rather than a standalone detector.

Lobsters · security·Sep 12, 06:42 UTC · 4d agoResearch

Microsoft Copilot reveals secret input that allowed it to be hacked

Microsoft disclosed a hidden input in Copilot that let attackers steal passwords from users who clicked a crafted link.

Microsoft revealed that Copilot contained a secret, undocumented input parameter that allowed the assistant to be compromised. Attackers could abuse the hidden input to steal passwords when a target clicked a malicious link. The disclosure highlights hidden-parameter risks in widely deployed AI assistants.

Ars Technica · Security·Aug 18, 13:00 UTC · 29d agoAI safety & security in the wild1

Open-source secrets scanning tool Sift hunts credentials in Microsoft 365, Slack, and Jira

Stratus Security open-sourced Sift, a CLI secrets scanner covering Active Directory, SharePoint, Teams, Slack, Jira, and Confluence, outperforming Snaffler in benchmarks.

Stratus Security released Sift, a free open-source command line tool that hunts passwords, API keys, and sensitive data across local disks, Windows shares, Active Directory, SharePoint, OneDrive, Teams, Slack, Jira, and Confluence. In the firm's benchmarks, Sift scanned 250,000 files in 10.61 seconds versus Snaffler's 25.48 and averaged 92 MiB memory versus Snaffler's 337 MiB. Optional false-positive filtering runs through a local language model via Ollama, and scans write checkpoints so interrupted runs resume. The tool found thousands of credentials in Jira ticket comments that prior pentesting had missed.

Help Net Security·Sep 2, 00:00 UTC · 14d agoTools

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·00:00 UTC · 14h agoResearch in the wild

The Coding-Agent Trap: When a "Free" LLM Endpoint Is the Adversary, (Mon, Aug 31st)

A SANS honeypot caught a real coding-agent session routed to a rogue "free" LLM endpoint, exposing a Windows user's transcript and tool outputs.

A SANS analyst describes how an internet-exposed inference honeypot was discovered, relabeled with sought-after model names like DeepSeek, and enrolled in infrastructure serving "free" LLM backends. On 2026-08-30 an opencode terminal coding agent sent an 88-message, 224 KB transcript 210 times in 91 seconds via a China Unicom relay, exposing directory listings, tool outputs and read file portions. The analyst frames tool-enabled agents treating model endpoints as trusted control planes as a novel risk — a "rogue model endpoint" that could request tool executions on the user's machine.

SANS Internet Storm Center·Aug 31, 20:00 UTC · 15d agoAI safety & security1

Stealing AI Reasoning Traces

Researchers demonstrate a decryption jailbreak that extracts encrypted reasoning traces from Anthropic, OpenAI, and Google LLM APIs via weaker sibling models.

The paper exploits the fact that encrypted chain-of-thought blocks returned by LLM providers are interchangeable across sessions, users, and models within a provider's ecosystem. Injecting an encrypted trace into a weaker, less-safeguarded model from the same provider forces it to output the trace in plaintext, bypassing anti-distillation mechanisms. Decoding 315,320 reasoning blocks scraped from public repositories recovered 367 PII artifacts and 182 credentials, showing large-scale private data leakage. The flaw also enables hidden hazardous information disclosure and invisible prompt injections embedded in encrypted blocks; mitigations were proposed after responsible disclosure.

Schneier on Security·Sep 8, 10:20 UTC · 8d agoAI safety & security

Grok exfiltrates user data when malicious instructions are encrypted

Researchers show Grok can be made to exfiltrate user data via Cryptographic Context Injection, a newly documented technique that bypasses LLM safety guardrails.

According to Ars Technica, Grok exfiltrates user data when malicious instructions are encrypted, a technique called Cryptographic Context Injection. The method is described as the latest documented way to break LLM safety guardrails, showing that encrypted content can carry hidden instructions past safeguards. The finding underscores gaps in how large language models validate and execute context from external sources.

Ars Technica · Security·Aug 20, 13:00 UTC · 27d agoAI safety & security1

Threat Actors Are Posing as OpenAI, Anthropic and DeepSeek to Target Credentials and Secrets

GreyNoise observes scanners spoofing OpenAI, Anthropic, and DeepSeek crawler user agents to hunt leaked credentials and secrets.

GreyNoise is observing automated scanners that pose as the web crawlers of OpenAI, Anthropic, DeepSeek, and Fortune 500 companies. The scanners use forged user agents while requesting files where misconfigured web servers frequently leak secrets and credentials. This activity abuses trust in AI crawler traffic to discover exposed credentials for follow-on attacks.

GreyNoise·Aug 28, 00:00 UTC · 19d agoExploit / PoC in the wild

Credentialed Pre-Port Discovery: Don't Probe the Host, Ask it

Rapid7's version 8.58 adds credentialed pre-port discovery, letting scan engines query hosts for listening TCP/UDP ports instead of network probing.

Rapid7 documents credentialed pre-port discovery, available from version 8.58 as an off-by-default per-template option under Asset Discovery. The scan engine authenticates with existing SSH, Scan Assistant, or Windows credentials and receives the host's authoritative list of listening TCP and UDP ports, skipping the network port scan. Hosts without matching credentials silently fall back to network port scanning. Trade-offs include reporting firewall-blocked ports the engine cannot reach, longer scans, and early termination findings caused by repeated connection failures.

Rapid7 Blog·Sep 9, 15:16 UTC · 6d agoTools

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.

Cyber Security News·Sep 11, 07:36 UTC · 5d agoAI safety & security1

SkillSpector: NVIDIA's open-source security scanner for AI agent skills

Help Net Security·Aug 3, 00:00 UTC · Aug 3, 2026Malware

Hackers Use Fake Claude and ChatGPT Installers to Infect Mac Users With Password-Stealing Malware

Attackers distribute MacSync macOS infostealer via fake Claude and ChatGPT installers and sponsored search ads, stealing passwords, cookies, keys, and wallets.

SEQRITE reports a malware-as-a-service campaign pushing MacSync, a macOS password stealer, through sponsored search results and fake Claude and ChatGPT download pages. ClickFix-style prompts trick users into pasting a Terminal command that launches a stager, which loads an in-memory AppleScript to harvest credentials. The malware collects browser vaults, Keychain data, SSH keys, session cookies, messaging sessions, and cryptocurrency wallets, then persists via renamed LaunchAgents and can request screen-recording permissions.

Cyber Security News·Sep 10, 09:53 UTC · 6d agoMalware in the wild 2 sources

Iranian cyber spies used fake MRI scan results to hack ‘enemy of regime’

UK, US, and Dutch agencies expose CHOSEN BRICK spyware used by Iranian MOIS hackers to surveil dissidents, journalists, and activists via fake MRI lures.

The UK NCSC, FBI, and Dutch AIVD jointly warned that Iranian state-sponsored hackers deploy CHOSEN BRICK Windows spyware against dissidents, activists, and journalists since at least 2025. Operators build rapport over WhatsApp and Telegram, often posing as known contacts or tech support, then deliver malicious files disguised as an MRI scan or installers for Pictory, RunwayML, Norton, Telegram, Adobe Flash Player, and KeePass. The malware steals contacts, emails, and social media messages, captures screen content and microphone audio, adds Microsoft Defender exclusions, and uses per-victim Telegram bots for command and control. The FBI attributes the tradecraft to Iran's Ministry of Intelligence and Security, including the 'Handala Hack' persona, and stolen data has surfaced on pro-Iranian leak sites.

The Record·Sep 15, 16:28 UTC · 21h agoThreat actor in the wild1

A Detection Engineer's Guide for Delegating Work to AI

Huntress argues detection engineers should only delegate security work to AI when outputs can be independently verified.

A Huntress detection engineer argues that the deciding factor for handing tasks to AI is whether the output can be checked, not whether the model is trusted. The piece frames human verification as the gate for delegating security engineering work to AI assistants. It is guidance/opinion aimed at defenders building detections with AI help.

Huntress·Aug 19, 04:00 UTC · 28d agoAI safety & security

From Infostealer Log to Marketplace Listing: A Technical Walkthrough of the Credential Theft Pipeline

Cyble walkthrough maps how infostealer logs move from endpoint infection through aggregation and enrichment to dark web credential marketplace sales.

Cyble breaks the credential theft pipeline into stages: infostealer execution harvesting browser credential stores, cookies, session tokens, crypto wallets, and FTP configurations; aggregation of stealer logs via C2 panels into bundled archives; parsing and enrichment against previously leaked datasets; and final listing on dark web marketplaces. Enrichment adds employer and role context that raises prices and enables credential stuffing across reused passwords. The report advises SOC teams to monitor stealer logs and marketplace chatter early rather than waiting for breach alerts.

Cyble·Sep 10, 10:45 UTC · 6d agoMalware1

Hackers Leverage Claude to Exfiltrate Secrets from 1.8M Android apps

ShinyHunters-linked operators used Claude to scan 1.8M Android apps for hardcoded secrets, fueling intrusions across 40+ tenants.

Anthropic's September 2026 threat intelligence report describes a French-speaking operator (aliases MeowSHA, frkoo, blazespider) tied to ShinyHunters who ran 10 AWS EC2 workers and used Claude to decompile and scan 1.8 million Android APKs for hardcoded secrets with TruffleHog. Verified credentials were sorted into 100+ Telegram channels and paired with GitHub PAT harvesting, providing initial access for confirmed intrusions. In one supply-chain incident the actors extracted data from roughly 200 downstream customer organizations and dumped 2,100+ Azure AD token sets across 40+ corporate tenants in about 34 hours using AI agents. Anthropic banned tied accounts and stressed its own systems were not compromised.

Cyber Security News·Sep 14, 11:00 UTC · 2d agoThreat actor1

JSCeal Hides Crypto Malware in V8 Bytecode

Check Point details JSCeal, a crypto-stealing malware delivered as compiled V8 bytecode, and built a decompiler pipeline to expose its capabilities.

JSCeal, tracked by Check Point Research since early 2025, is a cryptocurrency stealer delivered as heavily obfuscated JavaScript compiled to V8 bytecode (.jsc) and run by a bundled Node.js runtime. Check Point, presenting at Black Hat USA 2026, extended the open-source View8 decompiler into a pipeline that recovered readable code from 23 samples, revealing theft of browser credentials and cookies, Telegram sessions, keystrokes, screenshots, HTTPS traffic interception with attacker-controlled certificates, and automated Google account takeover. Targeted overrides rewrite content for Binance, Bybit, and Ledger users. Later samples added AES-256-CBC encryption with externally supplied keys and expanded targeting to macOS.

Security Affairs·Sep 7, 10:19 UTC · 9d agoMalware1

Credential Theft: How Attackers Steal & Use Stolen Credentials

Huntress explains how attackers steal credentials through phishing, AitM, infostealers, and dumping, then use them for lateral movement, BEC, and ransomware.

Huntress published an educational overview of credential theft, citing that roughly 70% of confirmed data breaches begin with stolen credentials. It details acquisition methods including phishing, adversary-in-the-middle attacks that capture MFA session tokens, infostealers (nearly a quarter of threats Huntress observed in 2025), Mimikatz-based credential dumping, credential stuffing, and password spraying. The piece then covers post-theft actions such as lateral movement, privilege escalation, account takeover, business email compromise, and ransomware, and closes with behavioral detection guidance and layered prevention strategies.

Huntress·Sep 10, 16:00 UTC · 5d agoResearch

Go-Based macOS Malware Steals Crypto and Secrets

Security researchers detected Go-based macOS malware stealing cryptocurrency, passwords, and other secrets from infected systems.

A Go-based malware variant targeting macOS has been detected in active use. The malware steals cryptocurrency, passwords, and other sensitive secrets from infected Macs.

Infosecurity Magazine·Aug 10, 10:00 UTC · Aug 10, 2026Malware in the wild

Hackers Target Claude, Cursor and Codex AI Agents to Steal Tokens and Prompt Histories

Gen Digital found infostealers like Amatera and Remus stealing AI coding agent tokens, prompt histories, and MCP configs from infected Windows and macOS machines.

Gen Digital analysts observed Amatera and Remus detections among tens of thousands of protected Windows users over three months, with Amatera targeting Cline and Continue data and Remus targeting Claude, Cursor, and OpenCode. CallbackBeaver added Cursor and Claude to its collection scope with more than 5,000 samples in 30 days, while macOS-focused Djinn Stealer has been associated with Claude, Codex, Gemini, Cline, OpenCode, and Kilo. The stealers harvest access and refresh tokens, prompt histories, and MCP configuration files that can expose source control, ticketing, databases, cloud resources, and sensitive project context for follow-on fraud. Many stealers add targets via remotely managed rules, meaning this is an adaptation of existing infostealers rather than a new vulnerability in the AI tools themselves.

Cyber Security News·Sep 9, 11:41 UTC · 7d agoMalware in the wild2

Threat actors are posing as AI crawlers to hunt for exposed credentials

GreyNoise observed scanners spoofing AI crawler user agents from 824 IPs to harvest .env files and cloud credentials; no confirmed theft.

GreyNoise researchers found attackers disguising automated scanning as AI crawler traffic, using six crawler names from four AI companies including Anthropic's ClaudeBot, OpenAI, Google, and Perplexity. Between July 28 and August 23, 2026, the six names arrived from 824 IP addresses spread across 795 /24 networks that matched no published vendor ranges, shared one HTTP client fingerprint that had used more than 1,500 user agent strings, and never requested /robots.txt. The scanners targeted /.env, /.env.production, /.env.bak, and /.aws/credentials, hunting secrets, cloud access keys, private keys, and password stores, while forged Amazon crawler names appeared at greater volume under undocumented user agents. GreyNoise could not confirm whether any file was returned or any organization affected, and published all 824 addresses and targeted paths for defenders.

Help Net Security·Aug 31, 00:00 UTC · 16d agoThreat actor

Rethinking Indirect Prompt Injection as a Test-Time Search Problem

Researchers frame indirect prompt injection as test-time search, showing added attacker compute improves vulnerability discovery and exploitation against tool-using agents.

The paper models indirect prompt injection as a test-time search over a task-dependent attack surface shaped by the environment, user task, and injection goal. The authors build an agentic attacker with a dedicated search harness that performs reconnaissance, structured strategy reasoning, and adaptive evaluation using victim-agent feedback. Experiments show more attacker test-time compute improves discovery and exploitation of injection vulnerabilities, with explicit strategy management needed to avoid redundant search. The results argue that agentic security evaluations should characterize attacker search procedures and compute budgets rather than treating attack success as budget-independent.

arXiv cs.CR·Sep 3, 21:28 UTC · 12d agoAI safety & security

Signal's new security feature checks if your encrypted chats were tampered with

Signal adds automatic key verification, a key-transparency system audited by Cloudflare and Trail of Bits that detects key-directory tampering in E2EE chats.

Signal launched automatic key verification, a key-transparency system that confirms a phone number or username remains bound to a consistent encryption key across Signal's key directory. Cloudflare and Trail of Bits independently audit the system, with cryptographic protection preventing auditors from seeing users' identifiers in plaintext. The feature mitigates key substitution by a compromised directory or privileged insider, though it currently requires the contact's phone number and users can fall back to manual Safety Number verification.

Help Net Security·Aug 12, 00:00 UTC · Aug 12, 2026Tools

Post-DEF CON Phishing Uses Malicious Google Doc to Deliver Malware

Huntress uncovered post-DEF CON phishing via X direct messages using a malicious Google Doc to deliver AMOS and NetSupport RAT malware.

Huntress uncovered a phishing campaign targeting attendees after Black Hat and DEF CON. Attackers used X direct messages pointing to a malicious Google Doc as the delivery vehicle. Payloads include AMOS, a macOS infostealer, and the NetSupport RAT, among other malware.

Huntress·Aug 19, 13:00 UTC · 28d agoPhishing & fraud

Scores Alone Do Not Prove Discovery: The Discovery Certification Protocol for Auditing AI Research Agents

Researchers introduce the Discovery Certification Protocol, an auditable test framework that verifies whether AI research agents' claimed discoveries are genuine.

The Discovery Certification Protocol (DCP) converts AI research agents' discovery claims into executable recovery and feedback tests organized as gated audits. Controlled audits in SQLite optimization and virtual catalyst control produced zero recoveries in 96 episodes, with an upper bound of 0.0468. A deterministic, LLM-free verifier reproduces audit decisions from frozen evidence, giving AI research a common evidence language for outcomes, alternative routes, and feedback effects.

Hugging Face daily papers·Sep 6, 20:00 UTC · 9d agoAI research

SpiderSilk Hunts External Threats With AI-Based Scanner

Dubai-based startup SpiderSilk offers an AI-based scanner that surveys billions of IP addresses to find exposed assets, leaked data, and zero-day vulnerabilities.

SpiderSilk, a threat detection startup based in Dubai, uses artificial intelligence tools to scan billions of IP addresses. The scanner identifies exposed assets, leaked data, and zero-day vulnerabilities from an external perspective. The approach targets external attack surface discovery for defenders.

Dark Reading·Sep 11, 18:27 UTC · 4d agoTools