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Mallory
🇹🇷 TR

Bissa Scanner

Also known asbissa_scanner

Bissa scanner is a mature, modular exploitation and collection operation centered on React2Shell (CVE-2025-55182). Recovered artifacts showed infrastructure used for multi-victim exploitation, staging, review, and validation at scale. The operation scanned millions of internet-facing targets, logged more than 900 confirmed compromises, harvested tens of thousands of .env files, and used AI-assisted tooling including Claude Code and OpenClaw to troubleshoot, orchestrate, and refine exploitation and triage workflows. The workflow validated access, scored victims, and focused deeper follow-on activity on higher-value organizations, especially in financial, cryptocurrency, and retail sectors. The React2Shell payload was intended to enumerate .env files, cloud metadata, Kubernetes service account context, local credential stores, database and Redis access, and cryptocurrency wallet material. Stolen secrets included credentials for AI providers, cloud platforms, payment systems, messaging services, databases, authentication platforms, and collaboration services. The operation also used S3-compatible Filebase to archive harvested victim .env files. Researchers also recovered a WordPress module targeting CVE-2025-9501 in W3 Total Cache, but found only version-check logic and no evidence of successful exploitation through that module. Telegram artifacts tied the operation to the public handle @BonJoviGoesHard, display name "Dr. Tube," and to bots including @bissapwned_bot and @bissa_scan_bot used for alerting and AI-control functions. No nation-state attribution was stated in the provided content. Known aliases directly provided in the content: bissa_scanner.

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OPERATIONAL PROFILE

Targeting

Who, where, and (when attributed) which flag flies behind the operation. Pulled from open-source reporting and Mallory's analyst review.

Who they target

Sectors the actor has been observed targeting.

  • Financial Services
  • Consumer Discretionary Distribution & Retail

Where they're from

Attributed origin per open-source reporting.

  • TR
What this page doesn’t show

The version that knows your environment.

This page is what’s public. Mallory adds the parts that aren’t: sector and geo overlap with your footprint, the IOCs they’re burning right now, detection coverage, and what to do next.
Target overlap

Match sector + geo + tech-stack targeting against your real footprint.

Tradecraft mapping

Every observed MITRE ATT&CK technique, grouped by tactic.

Malware arsenal

Families this actor is known to deploy, with IOCs and behavior.

Exploited CVEs

CVEs this actor has used in known campaigns.

Detection signatures

YARA, Sigma, Snort, and vendor rules, auto-deployed to your SIEM.

Observables

Domains, IPs, and hashes tied to this actor, refreshed continuously.