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https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git
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Complete skill folder anatomy across all cybersecurity skills: - scripts/agent.py: 80-150 line Python agents using real libraries (impacket, boto3, azure-mgmt-*, kubernetes, pefile, yara, scapy, shodan, stix2, etc.) - references/api-reference.md: real API documentation with method signatures - LICENSE: MIT license for all skill folders
195 lines
6.7 KiB
Python
195 lines
6.7 KiB
Python
#!/usr/bin/env python3
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"""Forensic disk image analysis agent using The Sleuth Kit (TSK) command-line tools."""
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import subprocess
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import os
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import sys
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import json
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import csv
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import datetime
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def run_cmd(cmd):
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"""Execute a shell command and return output."""
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result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
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return result.stdout.strip(), result.stderr.strip(), result.returncode
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def get_image_info(image_path):
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"""Retrieve disk image metadata using img_stat."""
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stdout, _, rc = run_cmd(f"img_stat {image_path}")
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if rc == 0:
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info = {}
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for line in stdout.splitlines():
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if ":" in line:
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key, _, val = line.partition(":")
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info[key.strip()] = val.strip()
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return info
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return None
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def list_partitions(image_path):
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"""List partition layout using mmls."""
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stdout, _, rc = run_cmd(f"mmls {image_path}")
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partitions = []
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if rc == 0:
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for line in stdout.splitlines():
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parts = line.split()
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if len(parts) >= 6 and parts[2].isdigit():
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partitions.append({
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"slot": parts[0].rstrip(":"),
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"start": int(parts[2]),
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"end": int(parts[3]),
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"length": int(parts[4]),
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"description": " ".join(parts[5:]),
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})
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return partitions
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def list_files(image_path, offset, path="/", recursive=False):
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"""List files in a partition using fls."""
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flags = "-r" if recursive else ""
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cmd = f"fls {flags} -o {offset} {image_path}"
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if path != "/":
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cmd += f" -D {path}"
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stdout, _, rc = run_cmd(cmd)
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files = []
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if rc == 0:
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for line in stdout.splitlines():
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line = line.strip()
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if not line:
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continue
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parts = line.split("\t", 1)
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if len(parts) == 2:
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meta = parts[0].strip()
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name = parts[1].strip()
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deleted = meta.startswith("*")
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file_type = "d" if "d/" in meta else "r"
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inode = ""
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for token in meta.split():
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if "-" in token and token.replace("-", "").isdigit():
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inode = token
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break
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files.append({
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"name": name,
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"inode": inode,
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"type": "directory" if file_type == "d" else "file",
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"deleted": deleted,
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})
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return files
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def list_deleted_files(image_path, offset):
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"""List only deleted files using fls -rd."""
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stdout, _, rc = run_cmd(f"fls -rd -o {offset} {image_path}")
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deleted = []
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if rc == 0:
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for line in stdout.splitlines():
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line = line.strip()
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if line:
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deleted.append(line)
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return deleted
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def recover_file(image_path, offset, inode, output_path):
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"""Recover a file by inode using icat."""
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cmd = f"icat -o {offset} {image_path} {inode} > {output_path}"
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_, _, rc = run_cmd(cmd)
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return rc == 0
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def get_file_metadata(image_path, offset, inode):
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"""Get detailed file metadata using istat."""
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stdout, _, rc = run_cmd(f"istat -o {offset} {image_path} {inode}")
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return stdout if rc == 0 else None
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def create_bodyfile(image_path, offset, output_path):
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"""Generate a TSK bodyfile for timeline creation."""
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cmd = f'fls -r -m "/" -o {offset} {image_path} > {output_path}'
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_, _, rc = run_cmd(cmd)
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return rc == 0
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def generate_timeline(bodyfile_path, output_csv, start_date=None, end_date=None):
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"""Generate a timeline from a bodyfile using mactime."""
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cmd = f"mactime -b {bodyfile_path} -d"
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if start_date and end_date:
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cmd += f" {start_date}..{end_date}"
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cmd += f" > {output_csv}"
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_, _, rc = run_cmd(cmd)
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return rc == 0
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def search_keywords(image_path, offset, keyword):
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"""Search for keyword strings in the disk image."""
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cmd = f'srch_strings -a -o {offset} {image_path} | grep -i "{keyword}"'
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stdout, _, rc = run_cmd(cmd)
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return stdout.splitlines() if rc == 0 else []
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def find_file_signature(image_path, offset, hex_signature):
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"""Find file signatures at the sector level using sigfind."""
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stdout, _, rc = run_cmd(f"sigfind -o {offset} {image_path} {hex_signature}")
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return stdout if rc == 0 else None
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def analyze_image(image_path, case_dir):
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"""Run a full automated analysis workflow on a disk image."""
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os.makedirs(case_dir, exist_ok=True)
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results = {"image": image_path, "timestamp": datetime.datetime.utcnow().isoformat()}
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print(f"[*] Image info...")
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results["image_info"] = get_image_info(image_path)
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print(f"[*] Partition layout...")
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partitions = list_partitions(image_path)
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results["partitions"] = partitions
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for part in partitions:
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if "NTFS" in part.get("description", "") or "Linux" in part.get("description", ""):
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offset = part["start"]
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print(f"[*] Listing files at offset {offset} ({part['description']})...")
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files = list_files(image_path, offset, recursive=True)
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results[f"files_offset_{offset}"] = {
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"total": len(files),
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"deleted": sum(1 for f in files if f["deleted"]),
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}
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print(f" Total: {len(files)}, Deleted: {results[f'files_offset_{offset}']['deleted']}")
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print(f"[*] Creating bodyfile for timeline...")
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bf_path = os.path.join(case_dir, f"bodyfile_{offset}.txt")
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create_bodyfile(image_path, offset, bf_path)
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tl_path = os.path.join(case_dir, f"timeline_{offset}.csv")
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generate_timeline(bf_path, tl_path)
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report_path = os.path.join(case_dir, "analysis_summary.json")
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with open(report_path, "w") as f:
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json.dump(results, f, indent=2, default=str)
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print(f"[*] Summary saved to {report_path}")
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return results
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if __name__ == "__main__":
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print("=" * 60)
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print("Disk Image Forensic Analysis Agent")
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print("Tools: The Sleuth Kit (fls, icat, mmls, mactime)")
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print("=" * 60)
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if len(sys.argv) > 1:
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image = sys.argv[1]
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case = sys.argv[2] if len(sys.argv) > 2 else "/tmp/autopsy_case"
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if os.path.exists(image):
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analyze_image(image, case)
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else:
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print(f"[ERROR] Image not found: {image}")
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else:
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print("\n[DEMO] Usage: python agent.py <disk_image.dd> [case_directory]")
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print("[*] Supported operations:")
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print(" - Partition enumeration (mmls)")
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print(" - File listing with deleted file recovery (fls, icat)")
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print(" - Timeline generation (mactime)")
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print(" - Keyword searching (srch_strings)")
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print(" - File signature detection (sigfind)")
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