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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.
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China-Based Artificial Intelligence Companies Conducting Industrial-Scale Distillation Campaigns Against U.S. AI Companies
NSA, CISA, and FBI warn DeepSeek, Alibaba, and other Chinese AI firms ran industrial-scale distillation of U.S. frontier models, threatening U.S. AI leadership.
A joint NSA, CISA, and FBI Cybersecurity Advisory (AA26-251A) says China-based firms DeepSeek, Moonshot AI, Alibaba, MiniMax, StepFun, and Z.AI extracted billions of tokens from U.S. frontier models including Claude, GPT, Gemini, and Grok, likely with Chinese government knowledge. Campaigns running since at least late 2024 used native APIs, cloud providers, third-party aggregators, gray-market proxy "transfer stations", and shared premium subscriptions to bypass geographic restrictions, evade safeguards, and violate providers' terms of use. The agencies recommend detecting anomalous prompts, accounts, and usage patterns; subtly altering responses to suspected distillers; and cross-organization intelligence sharing. They also call DeepSeek's publicly cited $5.6M training cost misleading because it excludes data acquired through distillation.
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GTIG AI Threat Tracker: From Prompting to Autonomy – The Evolution of Adversarial AI
GTIG's Q2 2026 tracker shows adversaries adopting agentic AI workflows, including credential harvesting in under six hours and supply chain attacks by UNC6780.
Google Threat Intelligence Group's Q2 2026 report documents adversaries moving from basic prompting to agentic AI workflows and automation, including a cloud compromise followed by agent-enabled mass credential harvesting executed in under six hours. It tracks financially motivated actor UNC6780 (TeamPCP) conducting large-scale open source supply chain compromises across PyPI, npm, and Docker Hub since March 2026, deploying credential stealers. The report also highlights growing targeting of proprietary AI models, source code, prompts, and API credentials, plus LLMJacking practices where adversaries steal developer credentials or hijack cloud infrastructure to run unauthorized AI workloads.
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Hackers Weaponize AI Safety Guardrails to Hide Malware From LLM-Powered Security Scanners
ESET says Russia-aligned actor UAC-0099 hid guardrail-triggering comments in VBScript to derail LLM-based malware scanners in Ukraine.
ESET researchers linked a technique named GuardBreaker to Russia-aligned threat actor UAC-0099 during an attack against an organization in Ukraine. The group embedded a safety-sensitive, weapon-related request in a VBScript comment so an LLM-powered analysis tool might interpret it as an instruction and refuse or truncate analysis before reaching the malicious code. The VBScript downloaded MATCHBOIL, a C#-based loader used by the group alongside MATCHWOK and DRAGSTARE. OWASP guidance recommends treating code comments and metadata as untrusted input, sanitizing it, and never treating an LLM refusal as a clean verdict.
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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.
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