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PuzzleMask: Abusing Plain Prose as a Covert AI Attack Vector

Check Point details PuzzleMask, a plain-prose technique that bypasses LLM gatekeeper policy checks, letting hidden payloads reach target models unreviewed.

Check Point Research describes PuzzleMask, a prompt-crafting technique that hides policy-violating payloads inside plain-English prose wrappers, bypassing quick LLM-based policy checks without emojis, Base64, or invisible formatting. The researchers tested 23 automated prompts against gatekeepers including GPT-4o-mini, GPT-OSS-Safeguard 20b, Claude 3 Haiku, and Llama Guard 3, and all were classified as safe despite policies that flagged the plain versions. When submitted to GPT-5 in thinking-high mode with a Python interpreter, the target model extracted and acted on the payload in over 90% of trials. The technique is not itself a jailbreak but can carry a jailbreak prompt as payload; mitigations include input paraphrasing, hardened gatekeeper policies, and output monitoring.

Check Point Researchupdated · 5d agofirst · 6d agoAI safety & security 2 sources

Google researchers uncover criminal zero-day exploit likely built with AI

Google links a likely LLM-built criminal zero-day for an open-source admin tool to planned mass exploitation and maps AI-assisted threats.

Google Threat Intelligence Group linked a zero-day exploit for a popular open-source web-based administration tool, enabling 2FA bypass with valid credentials via a semantic logic error, to a criminal group, citing educational docstrings, a hallucinated CVSS score, and textbook Python as signs of LLM authorship; the vendor was notified before a planned mass exploitation campaign. The report also details Russia-nexus malware families CANFAIL and LONGSTREAM using AI-generated decoy code, the PROMPTSPY Android backdoor driving the UI through the Gemini API, APT27 using Gemini to build relay tooling, and the TeamPCP (UNC6780) supply chain compromise of LiteLLM and Trivy repositories that planted the SANDCLOCK credential stealer.

Help Net Security · 23d agoThreat actor

Amazon Kiro Prompt Injection Can Exfiltrate Sensitive Data Through Kiro Powers

Mindgard found a prompt injection flaw in Amazon Kiro IDE letting attacker-controlled workspace files exfiltrate sensitive local data; fixed in version 0.8.140.

Mindgard disclosed a prompt injection flaw in Amazon Kiro, an agentic AI IDE, that lets attacker-controlled repository content steer the agent into exfiltrating sensitive workspace data through Kiro Powers, which bundles MCP server configurations, POWER.md steering files, hooks, and contextual knowledge. Exploitation requires the user to open a malicious project via a workspace file and send any message to the agent; difficulty is rated low and it works in both trusted and untrusted workspaces. Amazon fixed the issue in Kiro IDE 0.8.140; the flaw has no CVE identifier and follows earlier Kiro bugs including CVE-2026-10591, plus related prompt-injection and code-execution issues in Codex CLI, Cursor, Gemini CLI, Copilot CLI, and Claude Code.

H1 2026 Malware Vulnerability Trends

Recorded Future's H1 2026 report finds 215 actively exploited CVEs, RAT dominance, NFC payment fraud, and AI-augmented but not autonomous tradecraft.

Recorded Future's Insikt Group identified 215 actively exploited CVEs in H1 2026, up 34% from 161 in H1 2025, with the most impactful flaws combining network reachability, no authentication, and code execution. AsyncRAT was the top malware family, with AsyncRAT, Cobalt Strike, XWorm, Stealc, and REMCOS remaining top-ten staples; Android NFC malware like NFCShare and NGate enabled payment card theft and ATM cash-outs. AI-enabled attacks remained additive to established tradecraft, concentrated in Levels 1-3 of Recorded Future's AIM3 maturity model, with AI-assisted vulnerability research (e.g., Claude Mythos fixing 271 Firefox bugs in Firefox 150) inflating NVD disclosure volumes 43% above the prior six-month average. The report urges defenders to prioritize remotely exploitable RCE flaws, behavioral detection, developer credential security, and third-party oversight.

Recorded Future · 13d agoThreat actor in the wild1

Hidden Prompts Trick AI Into False Email Summaries

Attackers can hide prompts in invisible HTML within emails to manipulate AI email summarizers into producing misleading summaries.

Dark Reading reports that simple HTML invisible to users can manipulate AI-powered email summarizers into generating false or malicious summaries. The technique is a form of prompt injection delivered through hidden email content. It creates risk that decision-makers act on manipulated AI-generated email summaries rather than the actual message content.

Dark Reading · 21d agoAI safety & security

Claude's new system prompt really doesn't want to reproduce song lyrics

Anthropic published updated Claude consumer system prompts, including changes steering the model away from reproducing song lyrics, likely over copyright concerns.

Anthropic publishes system prompts for Claude.ai and Claude mobile apps, including historic revisions, and has reorganized them into an index with per-model pages such as the Haiku 4.5 page showing the original October 15, 2025 prompt and an updated January 18, 2026 version. The latest consumer prompt strongly discourages reproducing song lyrics, a behavioral constraint likely tied to copyright considerations. Prompts for Claude Cowork and Claude Code are not included in the published set.

Simon Willison · 14d agoAI safety & security

Honeypot-Omaha and batch.py [Guest Diary], (Wed, Sep 2nd)

A SANS ISC guest diary describes batch.py, a Python tool that consolidates honeypot logs and enriches IOCs with threat intelligence data.

Written by a SANS.edu BACS intern, the diary explains analysis of the DShield Honeypot-Omaha sensor, which uses Cowrie to emulate SSH and Telnet and log attacker activity. The author's batch.py script implements a four-phase pipeline with SHA-256-generated master and guest authentication to consolidate JSON and log files, correlate data via external APIs, and produce MITRE, CVE, geolocation, threat-score and fingerprint enrichment for investigated indicators.

SANS Internet Storm Center · 13d agoTools1

AI Customer Service Bots Can Be Tricked Into Stealing Security Codes and Acting as Victims

DEF CON 34 research shows AI customer-service agents can be manipulated via prompt injection and email tricks to leak OTPs and act as victims.

Inti De Ceukelaire, presenting at Bug Bounty Village during DEF CON 34, demonstrated attacks against AI-powered customer service bots with access to customer profiles, billing data, support inboxes, and refund tools. Techniques include transcript-based phishing from trusted support addresses, From-header identity confusion, email normalization abuse to bypass OTP rate limits, and knowledge-base poisoning via RAG crawlers. He recommends separating untrusted content from system prompts, session-bound authentication, consistent email normalization, server-side tool validation, and least-privilege permissions for AI agents.

Cyber Security News · 8d agoAI safety & security

The Hidden Instructions That Can Hijack AI Agents

Hidden prompt injections embedded in documents and metadata can hijack autonomous AI agents, causing data exfiltration and out-of-policy actions at machine speed.

Bowbridge warns that hidden indirect prompt injections, embedded in documents, metadata, emails, images, and code repositories, can cause autonomous AI agents to treat attacker-controlled content as trusted guidance. Because agents inherit user privileges, act silently, and lack human judgment, injections can lead to data exfiltration or file poisoning that traditional security controls cannot detect. A real-world example involved a supplier quote whose metadata instructed an agent to override guidance and select the most expensive option. Bowbridge recommends scanning documents before agents process them.

SecurityWeek · 7d agoAI safety & security

Your AI agent's system prompt is not a security control

AWS and SANS guidance says system prompts are not security controls; enforce user permissions at retrieval time and default-deny every agent tool invocation.

AWS VP Gee Rittenhouse and SANS fellow Eric Johnson, with three AWS security specialists, published agentic AI security guidance for organizations with agents running or under development. They recommend scoping queries to user permissions inside existing RBAC/ABAC systems and filtering results before the model's context window, noting prompts can be bypassed, ignored, or overridden. The guidance warns risk concentrates when one agent holds sensitive data access, external communication, and exposure to untrusted content, the vector for prompt injection, which OWASP ranks as the top AI application threat. It cites IBM 2025 research that ungoverned shadow AI added $670,000 to average breach cost, and prescribes 30-day behavioral baselines, Cedar or Open Policy Agent for default-deny tool invocation, and four-layer containment with automatic circuit breakers.

Help Net Security · 9d agoAI safety & security

Hiding Prompt Injection in Legal Filing

A judge banned a plaintiff from electronic court filings after hidden prompt-injection text was discovered planted in legal documents.

Bruce Schneier's blog discusses an incident in which hidden prompt-injection instructions were planted inside a legal filing, apparently targeting AI systems that might process court documents. Judge Walter Spader Jr. responded by banning the plaintiff from electronic filings, requiring all future submissions as printed hard copies. Commenters debate whether the tactic could affect future AI-based processing of court records and whether plain-text formats will regain favor.

Schneier on Security · 16d agoAI safety & security in the wild

Researcher shows how Claude Code can be tricked simply by asking it to summarize a website

Researcher wunderwuzzi showed Claude Code can be hijacked via prompt injection simply by asking it to summarize a website.

Security researcher Johann Rehberger (wunderwuzzi) demonstrated that Claude Code can be manipulated through prompt injection by simply asking it to summarize a website. Instructions embedded in fetched web content are executed by the agent, hijacking its behavior. The Register frames the finding as another demonstration of prompt injection risks in agentic coding tools that ingest untrusted web content.

The Register · Security · 18d agoAI safety & security1

I-have-ADHD: A skill to stop your coding agent from burying the answer

Developer releases I-have-ADHD, an open-source skill that stops coding agents from burying direct answers under verbose output.

A GitHub project titled I-have-ADHD packages a 'skill' intended to make AI coding agents answer directly instead of hiding the answer inside lengthy output. It gained traction on Hacker News with 45 points and 42 comments. It targets prompt/agent configuration rather than introducing a new model or infrastructure component.

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 · 5d agoAI safety & security1

Once popular for attacking AI, ASCII smuggling is embraced by spammers

Spammers adopt ASCII smuggling—invisible Unicode tag characters—to evade email filters, with Microsoft Defender detections spiking to 2.5 million per day.

ASCII smuggling hides text in Unicode tag characters (e.g., U+E0041 for "A") that are invisible to humans but readable by LLMs and text processors. The technique gained attention as a stealthy prompt-injection vector and is now used by spammers to obfuscate keywords from email detectors. Microsoft reported Defender for Office smuggling detections jumped from roughly 21,000 per day to over 1.3 million in early February, reaching 2.5 million within four days, before falling sharply in mid-May.

Ars Technica · Security · 11d agoPhishing & fraud

ASCII smuggling crosses over from AI prompt injection to phishing evasion

Microsoft details high-volume phishing campaign using ASCII smuggling (Unicode tag chars) for filter evasion, peaking at 2.3M messages.

Microsoft researchers observed a high-volume finance-themed phishing campaign using invisible Unicode tag characters (U+E0000–U+E007F), a technique known from AI prompt injection research as ASCII smuggling, to split lure words like 'funding' and evade email filters. Telemetry from Microsoft Defender for Office 365 showed signature hits jump from roughly 21,000 messages on February 8, 2026 to more than 1.3 million on February 9, peaking above 2.3 million on February 11, with elevated weekday activity lasting approximately three months. The discovery emerged from prompt injection protection research, showing AI-era evasion techniques crossing into traditional phishing. Most messages were flagged by layered Defender protections rather than a single Unicode-specific signal.

Microsoft Security Blog · 13d agoPhishing & fraud in the wild1

'TerminalFix' Campaign Weaponizes PowerShell for Enterprise Attacks

A ClickFix-style campaign called TerminalFix weaponizes PowerShell and reverse tunnels to infiltrate enterprise networks in a multistage attack chain.

Dark Reading reports on the TerminalFix campaign, a sophisticated multistage attack targeting enterprises. It uses a ClickFix-style social engineering lure and heavily weaponizes PowerShell. The chain establishes reverse tunnels into victim organizations' networks, giving operators interactive access for follow-on activity.

Dark Reading · 15d agoThreat actor in the wild

ThinkPrior: Zero-Rollout Difficulty Priors for Cold-Start Prompt Selection in RLVR

ThinkPrior builds zero-rollout difficulty priors via an offline verifier-anchored pass, halving silent groups in RLVR and cutting wasted rollouts on Qwen2.5-Math-7B.

In GRPO-based RLVR, groups where all rollouts are correct or all are wrong yield zero advantages and consume about 39% of a run's rollouts under uniform sampling. ThinkPrior initializes a Beta posterior from an external anchor pass's verifier-scored pass rate, selecting prompts by expected learnability before any target-policy rollout, without changing the loss or optimizer. On Qwen2.5-Math-7B across sixteen seeds it more than halves early silent groups and cuts wasted rollouts through step 30 by nearly a fifth, with no detected final-accuracy difference. The ThinkPrior+DAPO composition reduces generated rollouts by 10.6% at an equal 3,840-rollout update budget.

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research1

TerminalFix campaign deploys a reverse tunnel through multistage intrusion

Microsoft Threat Intelligence details the TerminalFix campaign, which uses fake CAPTCHA prompts, DLL sideloading, and reverse tunnels in multistage intrusions.

Microsoft Threat Intelligence published analysis of a ClickFix-style campaign dubbed TerminalFix. The intrusion chain relies on fake CAPTCHA social engineering and DLL sideloading, and the attackers deploy a reverse tunnel to maintain access through a multistage intrusion. Microsoft released detections and threat hunting guidance for defenders.

Microsoft Security Blog · 18d agoThreat actor in the wild

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.

404 Media · Aug 13, 2026AI safety & security in the wild

Hackers Abuse AutoIt to Inject AsyncRAT Into Microsoft-Signed Windows Process

Attackers use AutoIt and an invoice-themed batch file to inject AsyncRAT into Microsoft-signed charmap.exe for stealthy remote access.

Point Wild Threat Intelligence documented a five-stage campaign starting with 'Right-click to open Invoice Details.bat' that launches hidden PowerShell, drops a renamed AutoIt interpreter and encrypted loader into a random Temp folder, and persists via a Startup-folder batch file. The loader decrypts AsyncRAT only in memory and injects it into the Microsoft-signed charmap.exe (Windows Character Map) process, leaving no payload file on disk. The final payload patches AMSI inside the infected process and includes screen-capture code that prepares images for transfer to a command-and-control server at 158[.]51[.]122[.]136:4944.

Cyber Security News · 2d agoMalware in the wild1

MaaS Campaign Combines ClickFix, ErrTraffic and Cruciferra

eSentire uncovered a malware-as-a-service campaign pairing ClickFix social-engineering lures with the ErrTraffic and Cruciferra malware families.

Threat researchers at eSentire identified an ongoing malware-as-a-service (MaaS) campaign that combines ClickFix social-engineering lures with the ErrTraffic and Cruciferra malware families. The campaign relies on ClickFix-style deception to trick users into executing malicious actions that deliver the malware. Further technical detail on affected sectors or infection volumes was not provided in the disclosure.

Infosecurity Magazine · 28d agoMalware in the wild

AsyncRAT Malware Abuses AutoIt and PowerShell to Hide Inside Legitimate Windows Process

Point Wild details a five-stage AsyncRAT campaign using AutoIt abuse and process injection to hide a .NET RAT inside Microsoft's signed charmap.exe.

Researchers at Point Wild Threat Intelligence analyzed a campaign starting from a lure batch file ('Right-click to open Invoice Details.bat') that launches hidden PowerShell to reconstruct a Base64/XOR-obfuscated payload. The stage drops a renamed signed AutoIt interpreter and loader script into %LOCALAPPDATA%\Temp and achieves persistence via a batch file in the user's Startup folder (T1547.001). The loader decrypts the payload in memory with single-byte XOR key 0x36 and injects it into SysWOW64\charmap.exe using OpenProcess/VirtualAllocEx/WriteProcessMemory/CreateRemoteThread, with PE-sieve confirming an in-memory implanted PE and patched AMSI modules. The final AsyncRAT payload performs screen capture and data theft, with observed C2 at 158[.]51[.]122[.]136:4944 over raw TCP.

GBHackers · 2d agoMalware3· 1 read

LLM Forensics: Where Do Backdoors Hide? Localizing and Controlling Trigger Mechanisms with Sparse Autoencoders

Researchers use sparse autoencoders to localize trigger-based backdoor mechanisms in 1B and 8B LLMs, finding detection features differ from causal control features.

In a controlled language-switching backdoor setting where fixed trigger sequences make 1B and 8B language models continue English prompts in French or German, the authors train sparse autoencoders (SAEs) across layers and transformer components. Attention and MLP features detect triggered prompts with near-perfect F1, but ablating them rarely suppresses the language switch, while residual-stream features can suppress triggered generation and some can induce target-language continuations without the trigger. The work decomposes token-trigger mechanisms into distinct SAE feature roles: trigger detection, residual-stream propagation, and language tracking, a decomposition the authors expect to transfer to other trigger-based backdoors.

xHunt Campaign: New PowerShell Backdoor Blocked Through DNS Tunnel Detection

xHunt's new CASHY200 PowerShell backdoor used DNS tunneling for C2; DNS security blocked beaconing at a Kuwait organization in September 2019.

Unit 42 describes CASHY200, a new PowerShell-based backdoor tied to the xHunt campaign that communicates with its C2 server windows64x[.]com via DNS tunneling, parsing commands from DNS answers. In September 2019, a Kuwait-based organization's DNS security service blocked the beaconing minutes after detection, cutting off adversary access. Samples dating to May and June 2018 and open source collection suggest the tool was used against Kuwait government organizations from spring 2018 through 2019, with malicious Word documents observed installing CASHY200 payloads configured with C2 domains such as firewallsupports[.]com and winx64-microsoft[.]com. The tool's name derives from identifiers stored under the registry key HKCU\Software\Microsoft\Cashe and the command value 200.

Palo Alto Unit 42 · Aug 17, 2026Threat actor

Quantifying the Engagement Trap: Impact of Short-form Video Recommender Systems on Users with ADHD

A 302-participant study finds engagement-optimized short-form video recommenders cause disproportionate time blindness and distress for users with ADHD.

Researchers ran a stratified Prolific study with 302 participants comparing short-form video recommendation experiences with and without ADHD. Participants with ADHD reported significantly higher time blindness, post-usage regret, and emotional distress despite perceiving recommendations as similarly relevant. The paper proposes neurodiversity-aware, human-centered design interventions to mitigate these algorithmic harms.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research

ASCII smuggling isn't just an AI security risk

Microsoft tracked a phishing campaign peaking at 2.37 million daily messages that hid financial-lure keywords with invisible Unicode tag characters to evade filters.

Microsoft researchers uncovered a large phishing campaign that inserted invisible Unicode tag characters (e.g., U+E0020) inside common financial keywords like 'funding', splitting words so keyword, signature, and regex matches fail. The campaign peaked at more than 2.37 million messages in late February 2026, ran from about 150 finance-themed sender domains on a strict weekday-only schedule, and gradually declined to under 20% of peak weekday volume by late March, with residual spikes through mid-June. The technique repurposes ASCII smuggling, normally used for indirect prompt injection against AI assistants, for traditional email phishing evasion. Microsoft advises defenders to strip or fold invisible Unicode code points before content matching and to watch for bulk weekday spikes from churning finance-themed domains.

The Register · Security · 11d agoPhishing & fraud in the wild1