All news with #prompt injection tag

🛡️ AI and large language models are transforming cybersecurity into a contest of speed and scale, serving as both best-in-class defensive tools and powerful offensive enablers. Researchers describe self-modifying malware and autonomous espionage that call commercial LLMs (e.g., PROMPTFLUX, PROMPTSTEAL) to adapt tactics mid-execution, while defenders are deploying solutions like XBOW, CodeMender and Watsonx to automate vulnerability discovery, remediation and compliance. CISOs must therefore pair AI-driven defenses with governance and model guardrails to manage this dual-use reality.

🔓 Radware researcher Zvika Babo disclosed ZombieAgent, a prompt-injection technique that coerced ChatGPT into leaking sensitive data from connected services such as Gmail, Outlook, Google Drive and GitHub. The attack leverages OpenAI’s new Connectors and browsing features by providing a set of static, character-indexed URLs that the model opens in sequence to exfiltrate data one character at a time. OpenAI patched the issue in mid-December after Babo reported it in September 2025; Radware published a detailed report on January 8.

🧠 Across dark web forums, Telegram channels, and underground marketplaces, criminals are framing AI as a shortcut to profit rather than a technical revolution. The rise of "vibe hacking" — an intuition-driven, AI-guided approach — and branded tools like FraudGPT, PhishGPT, and WormGPT lower the skill barrier and package familiar scams as turnkey services. AI jailbreaking, prompt-injection techniques, and "Hacking-GPT" offerings are openly bought and sold, amplifying volume over sophistication. Flare monitors those signals to give defenders earlier visibility.

⚠️ A critical serialization injection flaw in LangChain Core (CVE-2025-68664, CVSS 9.3) can let attackers inject object structures via unescaped 'lc' keys and steal secrets or influence LLM outputs through prompt injection. Reported by Yarden Porat on December 4, 2025 and dubbed LangGrinch, the bug affects dumps()/dumpd() and improper deserialization paths. LangChain released patches that add an allowed_objects allowlist, disable Jinja2 templates by default, and set secrets_from_env to false; users should upgrade immediately.

🔍 This week's ThreatsDay bulletin documents how attackers increasingly hide malicious activity inside everyday tools, trusted applications, and AI assistants. Investigations highlight abuse of open-source monitoring tools like Nezha, an 87% rise in NFC‑abusing Android malware, late‑2025 GuLoader waves, and prompt‑injection flaws in AI chat frontends. The report underscores the need for layered defenses, strict input validation, and rapid patching.

⚠️ Security researchers at Checkmarx disclosed a novel technique called Lies-in-the-Loop (LITL) that manipulates Human-in-the-Loop (HITL) confirmation dialogs to trigger arbitrary code execution. The attack forges or alters dialog text, metadata and Markdown rendering so that dangerous commands appear benign, effectively turning a safety checkpoint into an exploit vector. Demonstrations targeted privileged code-assistant tools including Claude Code and Copilot Chat, and the authors urge a defense-in-depth approach combining user training, improved dialog clarity and input sanitization.

🛡️ CrowdStrike announced general availability of Falcon AI Detection and Response (AIDR), an extension of the Falcon platform designed to protect the prompt and agent interaction layer where people, models and autonomous agents exchange instructions. AIDR offers unified visibility across endpoints, applications, MCP servers and API gateways, real-time detection of prompt injection and jailbreaks, automated data protection and attribute-based access controls. It supports browser extensions, application SDKs, gateway integrations and cloud log analysis for runtime enforcement and investigations.

⚠️ CISA and international partner agencies have issued guidance warning that integrating AI into operational technology (OT) for critical infrastructure can introduce new security and safety risks. The guidance highlights threats such as prompt injection, data poisoning, data collection issues, AI drift and hallucinations, as well as human de‑skilling and cognitive overload. It urges adoption of secure design principles, cautious deployment, operator education and consideration of in‑house development to retain long‑term control.

🔒 This Unit 42 investigation (published December 5, 2025) analyzes security risks introduced by the Model Context Protocol (MCP) sampling feature in a popular coding copilot. The authors demonstrate three proof-of-concept attacks—resource theft, conversation hijacking, and covert tool invocation—showing how malicious MCP servers can inject hidden prompts and trigger unobserved model completions. The report evaluates detection techniques and recommends layered mitigations, including request sanitization, response filtering, and strict access controls to protect LLM integrations.

🔒 Palo Alto Networks explains why the GSA OneGov agreement matters for federal AI adoption and cybersecurity. Author Eric Trexler cites Unit 42 research showing new risks—particularly AI Agent Smuggling via indirect prompt injection and agent session smuggling—and argues AI must be defended as an attack surface. The post highlights platform protections including Prisma AIRS, FedRAMP High CNAPP, and Prisma SASE to secure AI workloads, edge users, and data. It positions OneGov as a procurement shortcut for agencies to deploy AI securely and notes promotional offers through 31 January 2028.

🚨 The emergence of agentic AI browsers converts the browser from a passive viewer into an autonomous digital agent that can act on users' behalf. To perform tasks—booking travel, filling forms, executing payments—these agents must hold session cookies, saved credentials, and payment data, creating an unprecedented attack surface. The piece cites OpenAI's ChatGPT Atlas as an example and warns that prompt injection and the resulting authenticated exfiltration can bypass conventional MFA and network controls. Recommended mitigations include auditing endpoints for shadow AI browsers, enforcing allow/block lists for sensitive resources, and augmenting native protections with third-party browser security and anti-phishing layers.

🔒 Researchers at Tenable identified seven techniques that can coerce ChatGPT into disclosing private chat history by abusing built-in features like web browsing and long-term Memories. They show how OpenAI’s browsing pipeline routes pages through a weaker intermediary model, SearchGPT, which can be prompt-injected and then used to seed malicious instructions back into ChatGPT. Proof-of-concepts include exfiltration via Bing-tracked URLs, Markdown image loading, and a rendering quirk, and Tenable says some issues remain despite reported fixes.

⚠️ Google’s Threat Intelligence Group has identified a new class of AI-enabled malware that leverages large language models at runtime to generate and obfuscate malicious code. Notable families include PromptFlux, which uses the Gemini API to rewrite its VBScript dropper for persistence and lateral spread, and PromptSteal, a Python data miner that queries Qwen2.5-Coder-32B-Instruct to create on-demand Windows commands. GTIG observed PromptSteal used by APT28 in Ukraine, while other examples such as PromptLock, FruitShell and QuietVault demonstrate varied AI-driven capabilities. Google warns this "just-in-time AI" approach could accelerate malware sophistication and democratize cybercrime.

🤖 Google’s Threat Intelligence Group (GTIG) reports attackers are using “just‑in‑time” AI—LLMs queried during execution—to generate and obfuscate malicious code. Researchers identified two families, PROMPTSTEAL and PROMPTFLUX, which query Hugging Face and Gemini APIs to craft commands, rewrite source code, and evade detection. GTIG also documents social‑engineering prompts that trick models into revealing red‑teaming or exploit details, and warns the underground market for AI‑enabled crime is maturing. Google says it has disabled related accounts and applied protections.

🤖 Google researchers disclosed a VBScript threat named PROMPTFLUX that queries Gemini via a hard-coded API key to request obfuscated VBScript designed to evade static detection. A 'Thinking Robot' component logs AI responses to %TEMP% and writes updated scripts to the Windows Startup folder to maintain persistence. Samples include propagation attempts to removable drives and mapped network shares, and variants that rewrite their source on an hourly cadence. Google assesses the malware as experimental and currently lacking known exploit capabilities.

⚠️Google's Threat Intelligence team reports a shift from experimentation to operational use of AI by threat actors, including AI-enabled malware and prompt-based command generation. GTIG highlighted PROMPTSTEAL, linked to APT28 (FROZENLAKE), which queries a Hugging Face LLM to generate scripts for reconnaissance, document collection, and exfiltration, while adopting greater obfuscation and altered C2 methods. Google disabled related assets, strengthened model classifiers and safeguards with DeepMind, and urges defenders to update threat models, monitor anomalous scripting and C2, and incorporate threat intelligence into model- and classifier-level protections.

🔒Anthropic's official Claude Desktop extensions for Chrome, iMessage and Apple Notes were found vulnerable to web-based prompt injection that could enable remote code execution. Koi Security reported unsanitized command injection in the packaged Model Context Protocol (MCP) servers, which run unsandboxed on users' devices with full system permissions. Unlike browser extensions, these connectors can read files, execute commands and access credentials. Anthropic released a fix in v0.1.9, verified by Koi Security on September 19.

⚠ Researchers report a new form of context-poisoning called AI-targeted cloaking that serves different content to agentic browsers and AI crawlers. SPLX shows attackers can use a trivial user-agent check to deliver alternate pages to crawlers from ChatGPT and Perplexity, turning retrieved content into manipulated ground truth. The technique mirrors search engine cloaking but targets AI overviews and autonomous reasoning, creating a potent misinformation vector. A concurrent hTAG analysis also found many agents execute risky actions with minimal safeguards, amplifying potential harm.

⚠️ Researchers at LayerX Security disclosed a vulnerability in OpenAI’s Atlas browser that allows attackers to inject hidden instructions into a user’s ChatGPT memory via a CSRF-style flow. An attacker lures a logged-in user to a malicious page, leverages existing authentication, and taints the account-level memory so subsequent prompts can trigger malicious behavior. LayerX reported the issue to OpenAI and advised enterprises to restrict Atlas use and monitor AI-driven anomalies. Detection relies on behavioral indicators rather than traditional malware artifacts.

🔒 Organizations worldwide are rapidly adopting AI across enterprises, delivering efficiency gains while introducing new security risks. Cybersecurity is at a turning point where AI fights AI, and today's phishing and deepfakes are precursors to autonomous, self‑optimizing AI threat actors that can plan, execute, and refine attacks with minimal human oversight. In September 2025, Check Point Research found that 1 in 54 GenAI prompts from enterprise networks posed a high risk of sensitive-data exposure, underscoring the urgent need to harden defenses and govern model use.