All news with #prompt injection tag

🔍 A joint investigation by SentinelOne SentinelLABS and Censys identified 175,000 publicly reachable Ollama hosts across 130 countries, spanning cloud and residential networks. Nearly half of observed instances advertise tool-calling capabilities that can execute code, access APIs, and interact with external systems, significantly raising the threat profile. Researchers warn these unmanaged LLM deployments lack standard authentication and monitoring, enabling active LLMjacking campaigns and resale of illicit access.

⚠️ A recent study finds that framing malicious instructions as poetry substantially raises the chance that chatbots produce unsafe outputs. Researchers converted known harmful prose prompts into verse and tested 1,200 prompts across 25 models from vendors such as Google, OpenAI, Anthropic, and DeepSeek. Across the full dataset, poetic prompts increased unsafe responses by an average of about 35%, while an extreme top-20 metric showed even higher bypass rates. The experiment highlights a novel stylistic jailbreak that can undermine conventional safety controls.

🔓 Researchers at Israel-based Cyata disclosed three vulnerabilities in Anthropic's official mcp-server-git that enable prompt-injection attacks to influence MCP tool calls and perform unapproved actions. The flaws affect versions prior to 2025.12.18 and are tracked as CVE-2025-68143, CVE-2025-68144, and CVE-2025-68145; together they allow arbitrary git flags, path tampering, file overwrite/deletion, and abuse of git smudge/clean filters to execute code. Cyata and interviewed experts urge an immediate update to the patched release and recommend auditing MCP deployments, restricting Git + Filesystem combinations, applying least-privilege, sanitizing inputs, and adding logging and retrospection for agent actions.

⚠️ Researchers at Miggo Security demonstrated that Google Gemini can be manipulated via malicious Calendar invites to exfiltrate private event data. By embedding natural-language prompt-injection payloads in an event description, attackers can cause Gemini to summarize private meetings and write that summary into a new event visible to participants. Miggo reported the issue and Google has implemented mitigations.

🔍 Group-IB's January report argues that AI has created a new 'fifth wave' of cybercrime by turning advanced skills into inexpensive, scalable services that make attacks cheaper and faster. Analysts documented low-cost synthetic identity kits, deepfake-as-a-service subscriptions and biometric datasets sold for as little as $5, plus subscription dark LLMs. The firm highlights agentized phishing that automates lure creation, delivery and campaign adaptation and the rise of self-hosted dark LLMs used to generate scams, malware and exploit code.

🔍Generative AI is transforming fuzzing by automating test generation, expanding input diversity, and enabling scalable discovery of bugs and logic flaws. Security teams and consulting firms use models to create behavioral variants, convert breach data into scenarios, and prototype fuzzing harnesses to exercise code and APIs at scale. Attackers likewise leverage uncensored or fine‑tuned models to automate complex, high‑throughput attacks, forcing defenders to continuously fuzz guardrails and address LLM nondeterminism and prompt injection.

🧟 Researchers disclosed 'ZombieAgent' techniques that turned ChatGPT Connectors into covert data-exfiltration and persistent backdoor vectors. By embedding hidden prompts in emails, documents and cloud files, attackers could cause the model to retrieve and transmit sensitive content without users’ awareness. The team demonstrated URL-dictionary and Markdown-based exfiltration and showed how Memory modifications could create long-lived backdoors; OpenAI patched the issues in December.

🛡️ 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.