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Analyzing infostealer credential theft

Skill meltedinhex/analyst-ai-pack/skills/analyzing-infostealer-credential-theft

An open agent-skills library for malware analysis, reverse engineering, and threat hunting - 118 curated, runnable skills mapped to MITRE ATT&CK, D3FEND, and CAR.

Install
npx -y skills add meltedinhex/analyst-ai-pack --skill analyzing-infostealer-credential-theft

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What its author says it does

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Analyzes infostealer samples by mapping the browser, credential store, wallet, and application paths they target, and the exfiltration channel used, from static strings and behavior. Activates for requests to analyze an infostealer, identify targeted credential stores, or map stealer collection and exfiltration behavior.

The file declares its own license as Apache-2.0. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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Analyzing Infostealer Credential Theft

When to Use

  • You have an infostealer sample and need to enumerate what it targets: browser credential/cookie stores, crypto wallets, FTP/VPN/messaging app configs, and the exfil channel.
  • You are building detections from the file paths and endpoints a stealer references.

Do not use this to recover credentials yourself — it characterizes what the malware targets from inert static analysis.

Prerequisites

  • The sample (read inertly), optionally with extracted strings.

Safety & Handling

  • Read bytes statically; defang exfil endpoints; never run the stealer.

Workflow

Step 1: Map targeted artifacts

python scripts/analyst.py profile sample.bin

Matches references to known browser paths (Login Data, Cookies, Web Data), wallet directories, app config paths, and credential APIs, grouped by category.

Step 2: Identify exfiltration channel

Detects HTTP(S) POST endpoints, Telegram bot tokens, Discord webhooks, and FTP/SMTP usage in strings.

Step 3: Build the target/exfil profile

Summarize targeted stores and the exfil channel, mapping to ATT&CK.

Step 4: Defang and report

Defang endpoints and produce IOCs for detection.

Validation

  • Targeted artifacts are grouped (browsers, wallets, apps, system credential stores).
  • The exfil channel is identified with a defanged endpoint where present.
  • Findings map to ATT&CK credential-access/collection/exfiltration techniques.

Pitfalls

  • Generic browser paths can appear in benign tools — corroborate with theft behavior.
  • Missing wallet/app targets that use obfuscated path strings.
  • Reporting live exfil endpoints (webhooks, bot tokens) without defanging.

References

Keep looking

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