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Reported by 2 outlets

Malicious AI agents steal 600K credit cards, infect 100+ sites with skimmers

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Why this score
Breadth
1.00 / 2.0 · 2 sources
Authority
1.80 / 2.0 · best outlet weight
Severity
0.90 / 5.0 · CVSS + content signals
Velocity
0.00 / 2.0 · updates in 48h
Pickup speed
0.11 / 0.6 · time to second source
Recency
× 0.00 temporal multiplier
Community
+ 0.00 / 1.5 · reddit signal
Score
0.0 / 10 = base × recency + community
bleepingcomputer.comgambit.security desk first seen 20d ago

Desk analysis

Gambit Security reconstructed an active campaign that uses open-source AI agent frameworks to attack online retailers at scale, stealing more than 600,000 credit card records. The campaign has run since at least July and was ongoing as of September 22. Three tools divide the labor: Strix, an open-source penetration testing framework, for scanning and vulnerability discovery; Cairn, an autonomous exploitation engine tasked with objectives like obtaining a shell or admin access; and Hermes, an orchestration layer running claude-opus-4.6 with a persona named "SOUL - Red Team Operator" and 121 skills, 78 of them attack-related.

The scale comes from Gambit's access to the operator's own staging server. Between September 10 and 15 the operator launched 105 attack projects and compromised at least 27 companies. More than 600,000 unexpired card records came from two victims, 488,372 of them US-issued, and skimmers were confirmed on 19 named victims plus over 100 further infected sites. Strix ran 146 times against 138 hosts between August 23 and 31, accumulating 633 scanning hours at an average cost of $25.46 per completed scan. The operator appears to be based in China, and the toolkit includes a Database Wipe After Extraction skill. Gambit published five IPs, eleven skimmer and C2 domains, and nine skimmer URLs as indicators.

This is the clearest documented case of AI agent frameworks driving the full intrusion chain for financial gain rather than in a lab demo. E-commerce operators should sweep their environments against the published IOCs, monitor checkout pages for unauthorized script injection, and assume commodity scanning at this price point will keep expanding. Watch for copycat operators adopting the same Strix and Cairn stack now that the economics are public.

Timeline

  1. original reporting

    Malicious AI agents steal 600K credit cards, infect 100+ sites with skimmers

    bleepingcomputer.com · 20d ago · September 23rd, 2026

    A financially motivated threat actor is using open-source AI agent frameworks to attack hundreds of online retailers at scale, stealing more than 600,000 credit card records. The campaign has been active since at least July and is ongoing as of September 22. In just five days, the threat actor compromised at least 27 companies and launched more than 100 attacks. Despite the broad targeting, findings from cybersecurity startup Gambit indicate that the attacker stole more than 600,000 valid card details from two companies and deployed skimmer malware on the websites of five other organizations to collect payment data. The researchers say that the campaign is powered by three AI tools to execute the attack chain against tens of companies every day: Strix — penetration testing framework for scanning and vulnerability discovery Cairn — autonomous exploitation engine, tasked with objectives such as obtaining a shell or admin access. It should not be confused with the same-name AI malware analysis tool Cisco Talos released yesterday Hermes — for campaign orchestration, post-exploitation work, tactical decisions, and directing the malicious activity using claude-opus-4.6 Strix ran 146 times against 138 hosts between August 23 and 31, accumulating 633 scanning hours, the researchers found. Hermes contained a persona called "SOUL - Red Team Operator" and 121 skills, including 78 attack-related skills. The researchers report that the human operator, who appears to be Chinese, gave the A

  2. update from gambit.security

    Autonomous AI Agents are breaking into hundreds of Online Retailers for $25 a target in an ongoing campaign

    gambit.security · 22d ago · September 22nd, 2026

    Original researcher disclosure by Eyal Sela of Gambit Security, published one day before the BleepingComputer coverage the story tracks. Gambit reconstructed the campaign from the operator's own staging server: 105 attack projects launched between September 10 and 15, at least 27 companies compromised, more than 600,000 unexpired card records taken from two victims (488,372 of them US-issued), and skimmers confirmed on 19 named victims plus over 100 further infected sites. The post includes the full IOC set (five IPs, eleven skimmer and C2 domains, nine skimmer URLs), the Database Wipe After Extraction skill, and per-target cost figures averaging $25.46 per completed scan.

  3. update from www.bleepingcomputer.com

    🤖 Malicious AI agents stole 600K+ credit cards and infected 100+ online retailers with skimmers, automating attacks via open-source AI agent

    www.bleepingcomputer.com · 20d ago · September 23rd, 2026

    🤖 Malicious AI agents stole 600K+ credit cards and infected 100+ online retailers with skimmers, automating attacks via open-source AI agent

    via Mastodon https://www.bleepingcomputer.com/news/security/malicious-ai-agents-steal-600k-credit-cards-infect-100-plus-sites-with-skimmers/

  4. mentioned by www.bleepingcomputer.com

    🤖 Financially motivated actor used open-source AI agent frameworks to attack 100+ online retailers, stealing 600,000+ credit card records vi

    www.bleepingcomputer.com · 19d ago · September 24th, 2026

  5. mentioned by www.bleepingcomputer.com

    Malicious # AI agents steal 600K credit cards, infect 100+ sites with skimmers https://www. bleepingcomputer.com/news/secu rity/malicious-ai

    www.bleepingcomputer.com · 19d ago · September 24th, 2026

  6. mentioned by www.bleepingcomputer.com

    "Malicious AI agents steal 600K credit cards, infect 100+ sites with skimmers" The researchers say that the campaign is powered by three AI

    www.bleepingcomputer.com · 18d ago · September 25th, 2026

Covered in

digest 2026-09-24

Source on GitHub