Investigate malicious software delivered through trusted updates or dependencies. Compare suspect files with legitimate versions, examine signing anomalies and injected code, and organize evidence to assess the infection path and downstream impact.
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Investigate supply chain attack artifacts including trojanized software updates, compromised build pipelines, and sideloaded dependencies to identify intrusion vectors and scope of compromise.
实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Supply chain attacks compromise legitimate software distribution channels to deliver malware through trusted update mechanisms. Notable examples include SolarWinds SUNBURST (2020, affecting 18,000+ customers), 3CX SmoothOperator (2023, a cascading supply chain attack originating from Trading Technologies), and numerous npm/PyPI package poisoning campaigns. Analysis involves comparing trojanized binaries against legitimate versions, identifying injected code in build artifacts, examining code signing anomalies, and tracing the infection chain from initial compromise through payload delivery. As of 2025, supply chain attacks account for 30% of all breaches, a 100% increase from prior years.
pefile, ssdeep, hashlib#!/usr/bin/env python3
"""Compare trojanized binary against legitimate version."""
import hashlib
import pefile
import sys
import json
def compare_pe_files(legitimate_path, suspect_path):
"""Compare PE file structures between legitimate and suspect versions."""
legit_pe = pefile.PE(legitimate_path)
suspect_pe = pefile.PE(suspect_path)
report = {"differences": [], "suspicious_sections": [], "import_changes": []}
# Compare sections
legit_sections = {s.Name.rstrip(b'\x00').decode(): {
"size": s.SizeOfRawData,
"entropy": s.get_entropy(),
"characteristics": s.Characteristics,
} for s in legit_pe.sections}
suspect_sections = {s.Name.rstrip(b'\x00').decode(): {
"size": s.SizeOfRawData,
"entropy": s.get_entropy(),
"characteristics": s.Characteristics,
} for s in suspect_pe.sections}
# Find new or modified sections
for name, props in suspect_sections.items():
if name not in legit_sections:
report["suspicious_sections"].append({
"name": name, "reason": "New section not in legitimate version",
"size": props["size"], "entropy": round(props["entropy"], 2),
})
elif abs(props["size"] - legit_sections[name]["size"]) > 1024:
report["suspicious_sections"].append({
"name": name, "reason": "Section size significantly changed",
"legit_size": legit_sections[name]["size"],
"suspect_size": props["size"],
})
# Compare imports
legit_imports = set()
if hasattr(legit_pe, 'DIRECTORY_ENTRY_IMPORT'):
for entry in legit_pe.DIRECTORY_ENTRY_IMPORT:
for imp in entry.imports:
if imp.name:
legit_imports.add(f"{entry.dll.decode()}!{imp.name.decode()}")
suspect_imports = set()
if hasattr(suspect_pe, 'DIRECTORY_ENTRY_IMPORT'):
for entry in suspect_pe.DIRECTORY_ENTRY_IMPORT:
for imp in entry.imports:
if imp.name:
suspect_imports.add(f"{entry.dll.decode()}!{imp.name.decode()}")
new_imports = suspect_imports - legit_imports
if new_imports:
report["import_changes"] = list(new_imports)
# Check code signing
report["legit_signed"] = bool(legit_pe.OPTIONAL_HEADER.DATA_DIRECTORY[4].Size)
report["suspect_signed"] = bool(suspect_pe.OPTIONAL_HEADER.DATA_DIRECTORY[4].Size)
return report
def hash_file(filepath):
"""Calculate multiple hashes for a file."""
hashes = {}
with open(filepath, 'rb') as f:
data = f.read()
for algo in ['md5', 'sha1', 'sha256']:
h = hashlib.new(algo)
h.update(data)
hashes[algo] = h.hexdigest()
return hashes
if __name__ == "__main__":
if len(sys.argv) < 3:
print(f"Usage: {sys.argv[0]} <legitimate_binary> <suspect_binary>")
sys.exit(1)
report = compare_pe_files(sys.argv[1], sys.argv[2])
print(json.dumps(report, indent=2))
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Assess exposure of Windows secrets protected by DPAPI, the operating system’s data protection service, during authorized security tests. Guide examination and decryption of saved credentials and browser data using available user sessions, credentials, or backup keys.
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Assess Shadow Credentials account takeover during authorized Active Directory testing. Examine permissions that allow public key registration, validate authentication without a password reset, and document credential cleanup, detection opportunities, and access control changes needed for remediation.
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Prepare for CMMC Level 2, a cybersecurity certification for defense contractors. Define the systems handling controlled information, review security requirements, calculate the SPRS assessment score, and organize remediation plans and evidence into a readiness report.
中文简介正在准备中。当前显示英语简介。
Create disk images for investigations using dd or dcfldd on Linux. The workflow covers write protection, bit-for-bit copying, hash checks to verify integrity, and documentation of the acquisition process.
中文简介正在准备中。当前显示英语简介。
Review Active Directory permissions with ldap3, a Python library for directory queries. Identify excessive access granted to non-administrative accounts, explain potential privilege escalation paths, and produce a JSON report with affected objects and remediation recommendations.
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Inspect suspicious Android APK files without running them. Analyze permissions, app components, suspicious code patterns, and network indicators, then produce a JSON risk report to support malware triage and detection rule development.
中文简介正在准备中。当前显示英语简介。