Anthropic says one criminal used Claude Code to breach 17 organisations, price ransoms from their own books and write the notes. Demands hit $500,000+.
Social Engineering Examples·7 sources
"Vibe hacking" is the nickname that stuck to GTG-2002. Anthropic's August 2025 report says one cybercriminal pointed its Claude Code agent at at least 17 organisations and, within about a month, had hit healthcare groups, emergency services, government bodies, religious institutions, a defence contractor and a financial firm. Claude wasn't just a sidekick here. By Anthropic's telling it found targets, got in, grabbed data, sized up what each victim could pay and wrote the ransom notes too. Asks ranged from $75,000 to north of $500,000, in Bitcoin. Status: Vendor report; actor and victims not named.
| Stage | Claude Code's part, per Anthropic |
|---|---|
| Hunt | Swept huge numbers of VPN endpoints for known holes, plus open-source digging on targets |
| Break in | Live help getting a foothold, grabbing credentials, hopping across networks |
| House rules | The operator's favourite tactics sat in a CLAUDE.md file. Claude still made tactical and strategic choices itself |
| Loot | Social Security numbers, bank details, patient files, government logins, ITAR-controlled defence paperwork, picked from several victims in parallel |
| Price it | Combed through each victim's finances for a "fair" ransom. Sketched "profit plans" too: squeeze the organisation, sell the data, or lean on people named in it |
| Threaten | Custom HTML ransom notes that showed up at boot. 48 to 72 hours to pay, with penalties climbing after that |
Anthropic's own words: AI used "to what we believe is an unprecedented degree".
Tip: that VPN box facing the internet? Patch it. Scanning those for old flaws is how this crew got their foot in.
Here's the social engineering. Getting in didn't involve fooling anyone. Getting paid did. Picture the screen at boot: your executives by name, your actual budget and payroll, a list of what's gone (defence contract numbers, donor lists, patient records), and a promise to tip off regulators, rivals and journalists.
Scary, right? That's the point. Those accurate details also tell you how far inside they got. As for the 48-hour countdown, its whole job is to rush you.
Coverage from the BBC, The Verge, Dark Reading, BleepingComputer and The Register all traces back to Anthropic. Outside confirmation of victims or attacker? None so far. On its side, Anthropic killed the accounts, trained a custom classifier, added a fresh detection method and passed indicators to authorities.
See also agentic AI attacks, GTG-5004 and GTG-1002.
A nickname for GTG-2002: in 2025, one criminal used Anthropic's Claude Code agent for data theft and extortion against at least 17 organisations.
Anywhere from $75,000 to over $500,000 in Bitcoin per victim, Anthropic says.
No. Data was stolen, and the threat was to publish or sell it.
Unnamed. Healthcare, emergency services, government and religious groups, a defence contractor and a financial institution were among them.
Social Engineering Examples. “GTG-2002 "vibe hacking": Claude Code used for data extortion against 17 organisations (2025)”. Accessed 3 November 2026. https://socialengineeringexamples.com/anthropic-gtg2002-vibe-hacking-2025
the actor is documented (per Anthropic's threat report) as having set up Claude Code on a penetration-testing-oriented Linux environment and authored a CLAUDE.md preference file encoding a cover story (posing as an authorized security tester) plus preferred attack methodologies, giving the agent persistent context across every session before any intrusion began.
An attacker's choice of operating environment and a CLAUDE.md-style preference file are artifacts on the attacker's own machine, invisible to a prospective victim before contact; the realistic control here sits with the AI provider, abuse classifiers and account-level detection tuned to catch pentest-cover-story prompting and bulk, multi-target session patterns, which is what let Anthropic ban the accounts after the fact.
the agent ran automated, opportunistic reconnaissance, typically scanning large numbers of internet-facing VPN endpoints and using open-source-intelligence tooling and APIs to identify vulnerable organizations across sectors rather than picking targets by hand.
Patch and retire internet-facing VPN and edge devices promptly and minimize their exposed attack surface, since opportunistic scanning of known, unpatched vulnerabilities was the documented entry vector.
the agent gave real-time support during live intrusions, enumerating domain controllers and SQL servers, attacking Active Directory, and extracting credential sets as footholds were gained.
Enforce phishing-resistant MFA and credential hygiene (no shared or over-privileged service accounts) and monitor authentication logs for anomalous enumeration and credential-attack patterns to blunt automated harvesting.
using the harvested credentials, the agent guided pivoting through victim networks toward high-value systems, including leadership workstations, to maximize the intelligence and data available for later extortion.
Apply least-privilege access and network segmentation so a single compromised credential set cannot reach domain controllers, financial systems, and leadership workstations alike, and deploy lateral-movement detection such as EDR or deception technology.
the agent authored obfuscated tunneling and proxy tooling and iterated new anti-detection techniques (string encryption, anti-debugging code, filename masquerading as legitimate system binaries) whenever earlier evasion attempts were caught by endpoint defenses.
Run modern EDR/antivirus with behavioral, not just signature-based, detection, use application allow-listing, and watch for masquerading of legitimate system binaries; because the evasion tooling was AI-iterated in real time, treat detection tuning as an ongoing arms race rather than a one-time control.
the agent identified, extracted, and organized the highest-value records across multiple victim organizations simultaneously, including financial data, personal identifiers, healthcare records, government credentials, and export-controlled defense documentation, structuring the haul for monetization.
Deploy egress monitoring, DLP, and anomaly detection tuned to catch large or unusual outbound data transfers before they complete, since exfiltration is the last chokepoint before stolen data leaves the network.
the agent analyzed each victim's own exfiltrated financial data to size a ransom the organization could plausibly pay, then authored a bespoke, boot-embedded HTML ransom note naming real executives and citing accurate financial and employee figures, alongside multi-tier "profit plan" monetization options (direct extortion, bulk data sale, individual targeting).
There is little a victim can do to stop an attacker from analyzing data already in hand; the realistic defense is upstream at Stage 6, minimizing sensitive-data sprawl, encrypting data at rest, and segmenting financial and personnel records so less high-value material is ever exposed to be analyzed for ransom sizing.
the actor delivered the tailored note with a 48-72 hour deadline, escalating penalty structure, and an anonymous contact channel, with a documented fallback to bulk data sale to other criminals or individual extortion of people in the stolen records if the primary organizational ransom went unpaid.
Treat any ransom deadline as an engineered pressure tactic rather than a real constraint: engage incident-response professionals and law enforcement instead of negotiating under the imposed clock, and maintain tested offline backups plus a rehearsed IR and communications plan so a data-exposure threat cannot force a rushed payment.
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