vlad/reverse-skills-max
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

reverse-skills-max: initial public release (restored, redacted, hardened)

Browse Source
This commit is contained in:
baradok609hecl1pq6qi
2026-10-20 02:17:15 +03:00
commit da24c2bd20
2227 changed files with 443931 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

201
vendor-new/Anthropic-Cybersecurity-Skills/skills/performing-automated-malware-analysis-with-cape/LICENSE Normal file
View File

@@ -0,0 +1,201 @@
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
and distribution as defined by Sections 1 through 9 of this document.
"Licensor" shall mean the copyright owner or entity authorized by
the copyright owner that is granting the License.
"Legal Entity" shall mean the union of the acting entity and all
other entities that control, are controlled by, or are under common
control with that entity. For the purposes of this definition,
"control" means (i) the power, direct or indirect, to cause the
direction or management of such entity, whether by contract or
otherwise, or (ii) ownership of fifty percent (50%) or more of the
outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
exercising permissions granted by this License.
"Source" form shall mean the preferred form for making modifications,
including but not limited to software source code, documentation
source, and configuration files.
"Object" form shall mean any form resulting from mechanical
transformation or translation of a Source form, including but
not limited to compiled object code, generated documentation,
and conversions to other media types.
"Work" shall mean the work of authorship, whether in Source or
Object form, made available under the License, as indicated by a
copyright notice that is included in or attached to the work
(an example is provided in the Appendix below).
"Derivative Works" shall mean any work, whether in Source or Object
form, that is based on (or derived from) the Work and for which the
editorial revisions, annotations, elaborations, or other modifications
represent, as a whole, an original work of authorship. For the purposes
of this License, Derivative Works shall not include works that remain
separable from, or merely link (or bind by name) to the interfaces of,
the Work and Derivative Works thereof.
"Contribution" shall mean any work of authorship, including
the original version of the Work and any modifications or additions
to that Work or Derivative Works thereof, that is intentionally
submitted to the Licensor for inclusion in the Work by the copyright owner
or by an individual or Legal Entity authorized to submit on behalf of
the copyright owner. For the purposes of this definition, "submitted"
means any form of electronic, verbal, or written communication sent
to the Licensor or its representatives, including but not limited to
communication on electronic mailing lists, source code control systems,
and issue tracking systems that are managed by, or on behalf of, the
Licensor for the purpose of discussing and improving the Work, but
excluding communication that is conspicuously marked or otherwise
designated in writing by the copyright owner as "Not a Contribution."
"Contributor" shall mean Licensor and any individual or Legal Entity
on behalf of whom a Contribution has been received by the Licensor and
subsequently incorporated within the Work.
2. Grant of Copyright License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
copyright license to reproduce, prepare Derivative Works of,
publicly display, publicly perform, sublicense, and distribute the
Work and such Derivative Works in Source or Object form.
3. Grant of Patent License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
(except as stated in this section) patent license to make, have made,
use, offer to sell, sell, import, and otherwise transfer the Work,
where such license applies only to those patent claims licensable
by such Contributor that are necessarily infringed by their
Contribution(s) alone or by combination of their Contribution(s)
with the Work to which such Contribution(s) was submitted. If You
institute patent litigation against any entity (including a
cross-claim or counterclaim in a lawsuit) alleging that the Work
or a Contribution incorporated within the Work constitutes direct
or contributory patent infringement, then any patent licenses
granted to You under this License for that Work shall terminate
as of the date such litigation is filed.
4. Redistribution. You may reproduce and distribute copies of the
Work or Derivative Works thereof in any medium, with or without
modifications, and in Source or Object form, provided that You
meet the following conditions:
(a) You must give any other recipients of the Work or
Derivative Works a copy of this License; and
(b) You must cause any modified files to carry prominent notices
stating that You changed the files; and
(c) You must retain, in the Source form of any Derivative Works
that You distribute, all copyright, patent, trademark, and
attribution notices from the Source form of the Work,
excluding those notices that do not pertain to any part of
the Derivative Works; and
(d) If the Work includes a "NOTICE" text file as part of its
distribution, then any Derivative Works that You distribute must
include a readable copy of the attribution notices contained
within such NOTICE file, excluding any notices that do not
pertain to any part of the Derivative Works, in at least one
of the following places: within a NOTICE text file distributed
as part of the Derivative Works; within the Source form or
documentation, if provided along with the Derivative Works; or,
within a display generated by the Derivative Works, if and
wherever such third-party notices normally appear. The contents
of the NOTICE file are for informational purposes only and
do not modify the License. You may add Your own attribution
notices within Derivative Works that You distribute, alongside
or as an addendum to the NOTICE text from the Work, provided
that such additional attribution notices cannot be construed
as modifying the License.
You may add Your own copyright statement to Your modifications and
may provide additional or different license terms and conditions
for use, reproduction, or distribution of Your modifications, or
for any such Derivative Works as a whole, provided Your use,
reproduction, and distribution of the Work otherwise complies with
the conditions stated in this License.
5. Submission of Contributions. Unless You explicitly state otherwise,
any Contribution intentionally submitted for inclusion in the Work
by You to the Licensor shall be under the terms and conditions of
this License, without any additional terms or conditions.
Notwithstanding the above, nothing herein shall supersede or modify
the terms of any separate license agreement you may have executed
with Licensor regarding such Contributions.
6. Trademarks. This License does not grant permission to use the trade
names, trademarks, service marks, or product names of the Licensor,
except as required for reasonable and customary use in describing the
origin of the Work and reproducing the content of the NOTICE file.
7. Disclaimer of Warranty. Unless required by applicable law or
agreed to in writing, Licensor provides the Work (and each
Contributor provides its Contributions) on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied, including, without limitation, any warranties or conditions
of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
PARTICULAR PURPOSE. You are solely responsible for determining the
appropriateness of using or redistributing the Work and assume any
risks associated with Your exercise of permissions under this License.
8. Limitation of Liability. In no event and under no legal theory,
whether in tort (including negligence), contract, or otherwise,
unless required by applicable law (such as deliberate and grossly
negligent acts) or agreed to in writing, shall any Contributor be
liable to You for damages, including any direct, indirect, special,
incidental, or consequential damages of any character arising as a
result of this License or out of the use or inability to use the
Work (including but not limited to damages for loss of goodwill,
work stoppage, computer failure or malfunction, or any and all
other commercial damages or losses), even if such Contributor
has been advised of the possibility of such damages.
9. Accepting Warranty or Additional Liability. While redistributing
the Work or Derivative Works thereof, You may choose to offer,
and charge a fee for, acceptance of support, warranty, indemnity,
or other liability obligations and/or rights consistent with this
License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
of any other Contributor, and only if You agree to indemnify,
defend, and hold each Contributor harmless for any liability
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.
END OF TERMS AND CONDITIONS
APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "[]"
replaced with your own identifying information. (Don't include
the brackets!) The text should be enclosed in the appropriate
comment syntax for the file format. Please do not remove or change
the license header comment from a contributed file except when
necessary.
Copyright 2026 mukul975
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

182
vendor-new/Anthropic-Cybersecurity-Skills/skills/performing-automated-malware-analysis-with-cape/SKILL.md Normal file
View File

@@ -0,0 +1,182 @@
---
name: performing-automated-malware-analysis-with-cape
description: Deploy and operate the CAPEv2 malware sandbox (a Cuckoo derivative) to run samples in a
monitored Windows guest VM, capturing behavioral signatures, dropped files, PCAP network traffic,
and family-specific configuration extraction (e.g. Emotet, TrickBot, Cobalt Strike) via
cape-parsers. Use when a suspicious file or payload needs automated dynamic analysis, anti-evasion
debugger tricks, or config/payload extraction.
domain: cybersecurity
subdomain: malware-analysis
tags:
- cape
- sandbox
- automated-analysis
- malware-analysis
- behavioral-analysis
- payload-extraction
- cuckoo
version: '1.0'
author: mahipal
license: Apache-2.0
nist_csf:
- DE.AE-02
- RS.AN-03
- ID.RA-01
- DE.CM-01
mitre_attack:
- T1027
- T1055
- T1140
- T1497
- T1070
---
# Performing Automated Malware Analysis with CAPE
## Overview
CAPE (Config And Payload Extraction) is an open-source malware sandbox derived from Cuckoo that automates behavioral analysis, payload dumping, and configuration extraction. CAPEv2 features API hooking for behavioral instrumentation, captures files created/modified/deleted during execution, records network traffic in PCAP format, and includes 70+ custom configuration extractors (cape-parsers) for families like Emotet, TrickBot, Cobalt Strike, AsyncRAT, and Rhadamanthys. The signature system includes 1000+ behavioral signatures detecting evasion techniques, persistence, credential theft, and ransomware behavior. CAPE's debugger enables dynamic anti-evasion bypasses combining debugger actions within YARA signatures. Recommended deployment: Ubuntu LTS host with Windows 10 21H2 guest VM.
## When to Use
- When conducting security assessments that involve performing automated malware analysis with cape
- When following incident response procedures for related security events
- When performing scheduled security testing or auditing activities
- When validating security controls through hands-on testing
## Prerequisites
- Ubuntu 22.04 LTS server (8+ CPU cores, 32GB+ RAM, 500GB+ SSD)
- KVM/QEMU virtualization support
- Windows 10 21H2 guest image
- Python 3.9+ with CAPEv2 dependencies
- Network configuration for isolated analysis network
## Workflow
### Step 1: Submit and Analyze Samples via API
```python
#!/usr/bin/env python3
"""CAPE sandbox API client for automated malware submission and analysis."""
import requests
import json
import time
import sys
from pathlib import Path
class CAPEClient:
def __init__(self, base_url="http://localhost:8000", api_token=None):
self.base_url = base_url.rstrip("/")
self.headers = {}
if api_token:
self.headers["Authorization"] = f"Token {api_token}"
def submit_file(self, filepath, options=None):
"""Submit a file for analysis."""
url = f"{self.base_url}/apiv2/tasks/create/file/"
files = {"file": open(filepath, "rb")}
data = options or {}
data.setdefault("timeout", 120)
data.setdefault("enforce_timeout", False)
resp = requests.post(url, files=files, data=data, headers=self.headers)
resp.raise_for_status()
result = resp.json()
task_id = result.get("data", {}).get("task_ids", [None])[0]
print(f"[+] Submitted {filepath} -> Task ID: {task_id}")
return task_id
def get_status(self, task_id):
"""Check task analysis status."""
url = f"{self.base_url}/apiv2/tasks/status/{task_id}/"
resp = requests.get(url, headers=self.headers)
return resp.json().get("data", "unknown")
def wait_for_completion(self, task_id, poll_interval=15, max_wait=600):
"""Wait for analysis to complete."""
elapsed = 0
while elapsed < max_wait:
status = self.get_status(task_id)
if status == "reported":
print(f"[+] Task {task_id} completed")
return True
time.sleep(poll_interval)
elapsed += poll_interval
print(f" Waiting... ({elapsed}s, status: {status})")
return False
def get_report(self, task_id):
"""Retrieve full analysis report."""
url = f"{self.base_url}/apiv2/tasks/get/report/{task_id}/"
resp = requests.get(url, headers=self.headers)
return resp.json()
def get_config(self, task_id):
"""Get extracted malware configuration."""
report = self.get_report(task_id)
configs = report.get("CAPE", {}).get("configs", [])
return configs
def get_dropped_files(self, task_id):
"""List files dropped during analysis."""
report = self.get_report(task_id)
return report.get("dropped", [])
def get_network_iocs(self, task_id):
"""Extract network IOCs from analysis."""
report = self.get_report(task_id)
network = report.get("network", {})
iocs = {
"dns": [d.get("request") for d in network.get("dns", [])],
"http": [h.get("uri") for h in network.get("http", [])],
"tcp": [f"{h.get('dst')}:{h.get('dport')}"
for h in network.get("tcp", [])],
}
return iocs
def analyze_sample(self, filepath):
"""Full automated analysis pipeline."""
task_id = self.submit_file(filepath)
if not task_id:
return None
if self.wait_for_completion(task_id):
report = {
"task_id": task_id,
"config": self.get_config(task_id),
"network_iocs": self.get_network_iocs(task_id),
"dropped_files": len(self.get_dropped_files(task_id)),
}
return report
return None
if __name__ == "__main__":
if len(sys.argv) < 2:
print(f"Usage: {sys.argv[0]} <malware_sample> [cape_url]")
sys.exit(1)
url = sys.argv[2] if len(sys.argv) > 2 else "http://localhost:8000"
client = CAPEClient(url)
result = client.analyze_sample(sys.argv[1])
if result:
print(json.dumps(result, indent=2))
```
## Validation Criteria
- Samples submitted and analyzed within configured timeout
- Behavioral signatures triggered for known malware families
- Malware configurations extracted by cape-parsers
- Network traffic captured and IOCs extracted
- Dropped files and payloads collected for further analysis
- Anti-evasion bypasses effective against sandbox-aware malware
## References
- [CAPEv2 GitHub](https://github.com/kevoreilly/CAPEv2)
- [CAPE Sandbox Documentation](https://capev2.readthedocs.io/)
- [Automating Malware Analysis with CAPE](https://endsec.au/blog/building-an-automated-malware-sandbox-using-cape/)
- [Installing CAPEv2 on Ubuntu](https://medium.com/@rizqisetyokus/building-capev2-automated-malware-analysis-sandbox-part-1-da2a6ff69cdb)

25
vendor-new/Anthropic-Cybersecurity-Skills/skills/performing-automated-malware-analysis-with-cape/assets/template.md Normal file
View File

@@ -0,0 +1,25 @@
# Analysis Report Template - performing-automated-malware-analysis-with-cape
## Sample Information
| Field | Value |
|-------|-------|
| SHA-256 | |
| File Type | |
| Analysis Date | |
| Analyst | |
| Classification | TLP:AMBER |
## Findings
| Finding | Severity | Details |
|---------|----------|---------|
| | | |
## IOCs Extracted
| Type | Value | Context |
|------|-------|---------|
| | | |
## Recommendations
1.
2.
3.

204
vendor-new/Anthropic-Cybersecurity-Skills/skills/performing-automated-malware-analysis-with-cape/references/api-reference.md Normal file
View File

@@ -0,0 +1,204 @@
# API Reference: CAPE Sandbox Automated Malware Analysis
## Libraries Used
| Library | Purpose |
|---------|---------|
| `requests` | HTTP client for CAPE REST API v2 |
| `json` | Parse analysis reports and task metadata |
| `os` | Read `CAPE_URL` and `CAPE_API_KEY` environment variables |
| `time` | Poll task status until analysis completes |
## Installation
```bash
pip install requests
```
## Authentication
```python
import requests
import os
CAPE_URL = os.environ.get("CAPE_URL", "http://cape.example.com:8000")
CAPE_KEY = os.environ.get("CAPE_API_KEY", "")
headers = {"Authorization": f"Token {CAPE_KEY}"} if CAPE_KEY else {}
```
## REST API v2 Endpoints
| Method | Endpoint | Description |
|--------|----------|-------------|
| POST | `/apiv2/tasks/create/file/` | Submit a file for analysis |
| POST | `/apiv2/tasks/create/url/` | Submit a URL for analysis |
| GET | `/apiv2/tasks/list/` | List all analysis tasks |
| GET | `/apiv2/tasks/view/{id}/` | Get task status and metadata |
| GET | `/apiv2/tasks/report/{id}/` | Get full analysis report |
| GET | `/apiv2/tasks/report/{id}/lite/` | Get lightweight report |
| DELETE | `/apiv2/tasks/delete/{id}/` | Delete a task and its data |
| GET | `/apiv2/tasks/screenshots/{id}/` | Get analysis screenshots |
| GET | `/apiv2/tasks/procmemory/{id}/` | Get process memory dumps |
| GET | `/apiv2/files/view/sha256/{hash}/` | Look up file by SHA-256 |
| GET | `/apiv2/files/get/{sha256}/` | Download the sample binary |
| GET | `/apiv2/pcap/get/{id}/` | Download PCAP network capture |
| GET | `/apiv2/machines/list/` | List analysis VMs |
| GET | `/apiv2/cuckoo/status/` | Server status and version |
## Core Operations
### Submit a File for Analysis
```python
def submit_file(file_path, timeout_mins=5, machine=None):
files = {"file": open(file_path, "rb")}
data = {
"timeout": timeout_mins * 60,
"enforce_timeout": True,
"options": "procmemdump=yes,import_reconstruction=yes",
}
if machine:
data["machine"] = machine
resp = requests.post(
f"{CAPE_URL}/apiv2/tasks/create/file/",
files=files,
data=data,
headers=headers,
timeout=60,
)
resp.raise_for_status()
result = resp.json()
return result["data"]["task_ids"][0]
```
### Submit a URL for Analysis
```python
def submit_url(url, timeout_mins=3):
resp = requests.post(
f"{CAPE_URL}/apiv2/tasks/create/url/",
data={
"url": url,
"timeout": timeout_mins * 60,
"options": "procmemdump=yes",
},
headers=headers,
timeout=30,
)
resp.raise_for_status()
return resp.json()["data"]["task_ids"][0]
```
### Poll Task Until Complete
```python
import time
def wait_for_task(task_id, poll_interval=30, max_wait=600):
elapsed = 0
while elapsed < max_wait:
resp = requests.get(
f"{CAPE_URL}/apiv2/tasks/view/{task_id}/",
headers=headers,
timeout=30,
)
status = resp.json()["data"]["status"]
if status == "reported":
return True
if status in ("failed_analysis", "failed_processing"):
raise RuntimeError(f"Task {task_id} failed: {status}")
time.sleep(poll_interval)
elapsed += poll_interval
raise TimeoutError(f"Task {task_id} did not complete within {max_wait}s")
```
### Retrieve Analysis Report
```python
def get_report(task_id, lite=False):
endpoint = "lite" if lite else ""
resp = requests.get(
f"{CAPE_URL}/apiv2/tasks/report/{task_id}/{endpoint}",
headers=headers,
timeout=120,
)
resp.raise_for_status()
return resp.json()
```
### Extract Key Findings from Report
```python
def extract_findings(report):
info = report.get("info", {})
findings = {
"score": info.get("score", 0),
"duration": info.get("duration", 0),
"signatures": [],
"network_iocs": {"domains": [], "ips": [], "urls": []},
"dropped_files": [],
"yara_matches": [],
}
# Behavioral signatures
for sig in report.get("signatures", []):
findings["signatures"].append({
"name": sig["name"],
"severity": sig["severity"],
"description": sig["description"],
})
# Network IOCs
network = report.get("network", {})
findings["network_iocs"]["domains"] = [
d["domain"] for d in network.get("domains", [])
]
findings["network_iocs"]["ips"] = [
h["ip"] for h in network.get("hosts", [])
]
# YARA matches
for target_yara in report.get("target", {}).get("file", {}).get("yara", []):
findings["yara_matches"].append(target_yara["name"])
return findings
```
### Download Network PCAP
```python
def download_pcap(task_id, output_path):
resp = requests.get(
f"{CAPE_URL}/apiv2/pcap/get/{task_id}/",
headers=headers,
timeout=60,
)
resp.raise_for_status()
with open(output_path, "wb") as f:
f.write(resp.content)
```
## Output Format
```json
{
"info": {
"id": 42,
"score": 8.5,
"duration": 120,
"machine": {"name": "win10-01", "label": "win10-01"},
"started": "2025-01-15T10:30:00",
"ended": "2025-01-15T10:32:00"
},
"signatures": [
{"name": "ransomware_bcdedit", "severity": 5, "description": "Modifies boot configuration"},
{"name": "creates_exe", "severity": 3, "description": "Creates executable files on disk"}
],
"network": {
"hosts": [{"ip": "198.51.100.42", "country": "US"}],
"domains": [{"domain": "c2.evil.example.com", "ip": "198.51.100.42"}]
},
"target": {
"file": {
"name": "sample.exe",
"size": 245760,
"sha256": "a1b2c3d4e5f6..."
}
}
}
```

9
vendor-new/Anthropic-Cybersecurity-Skills/skills/performing-automated-malware-analysis-with-cape/references/standards.md Normal file
View File

@@ -0,0 +1,9 @@
# Standards Reference - performing-automated-malware-analysis-with-cape
## Applicable Standards
- MITRE ATT&CK Framework
- NIST SP 800-83 Guide to Malware Incident Prevention
- NIST SP 800-86 Guide to Integrating Forensic Techniques
## Related MITRE ATT&CK Techniques
See SKILL.md for specific technique mappings.

11
vendor-new/Anthropic-Cybersecurity-Skills/skills/performing-automated-malware-analysis-with-cape/references/workflows.md Normal file
View File

@@ -0,0 +1,11 @@
# Analysis Workflows - performing-automated-malware-analysis-with-cape
## Primary Workflow
```
[Sample Collection] --> [Static Analysis] --> [Dynamic Analysis] --> [IOC Extraction]
|
v
[Report Generation]
```
See SKILL.md for detailed step-by-step procedures.

288
vendor-new/Anthropic-Cybersecurity-Skills/skills/performing-automated-malware-analysis-with-cape/scripts/agent.py Normal file
View File

@@ -0,0 +1,288 @@
#!/usr/bin/env python3
"""CAPE Sandbox automated malware analysis agent.
Submits malware samples to a CAPE Sandbox instance via its REST API,
polls for analysis completion, and retrieves behavioral reports including
process trees, network activity, dropped files, and extracted configs.
"""
import argparse
import json
import os
import sys
import time
from datetime import datetime, timezone
try:
import requests
except ImportError:
print("[!] 'requests' library required: pip install requests", file=sys.stderr)
sys.exit(1)
def get_cape_config():
"""Return CAPE server URL and optional API token."""
server = os.environ.get("CAPE_URL", "http://localhost:8090")
token = os.environ.get("CAPE_API_TOKEN", "")
return server.rstrip("/"), token
def submit_file(server, token, file_path, timeout_minutes=5, machine=None):
"""Submit a file to CAPE for analysis."""
url = f"{server}/apiv2/tasks/create/file/"
headers = {"Authorization": f"Token {token}"} if token else {}
if not os.path.isfile(file_path):
print(f"[!] File not found: {file_path}", file=sys.stderr)
sys.exit(1)
data = {"timeout": timeout_minutes * 60}
if machine:
data["machine"] = machine
print(f"[*] Submitting {os.path.basename(file_path)} to CAPE...")
with open(file_path, "rb") as f:
resp = requests.post(
url,
files={"file": (os.path.basename(file_path), f)},
data=data,
headers=headers,
timeout=120,
)
resp.raise_for_status()
result = resp.json()
if result.get("error"):
print(f"[!] Submission error: {result.get('error_value', result['error'])}", file=sys.stderr)
sys.exit(1)
task_id = result.get("data", {}).get("task_ids", [None])[0]
if not task_id:
task_id = result.get("task_id") or result.get("data", {}).get("task_id")
print(f"[+] Submitted successfully, task ID: {task_id}")
return task_id
def submit_url(server, token, target_url, timeout_minutes=5):
"""Submit a URL to CAPE for analysis."""
url = f"{server}/apiv2/tasks/create/url/"
headers = {"Authorization": f"Token {token}"} if token else {}
data = {"url": target_url, "timeout": timeout_minutes * 60}
print(f"[*] Submitting URL: {target_url}")
resp = requests.post(url, data=data, headers=headers, timeout=60)
resp.raise_for_status()
result = resp.json()
task_id = result.get("data", {}).get("task_ids", [None])[0]
if not task_id:
task_id = result.get("task_id")
print(f"[+] Submitted, task ID: {task_id}")
return task_id
def poll_task_status(server, token, task_id, max_wait=600, interval=15):
"""Poll CAPE until the analysis task completes or times out."""
url = f"{server}/apiv2/tasks/status/{task_id}/"
headers = {"Authorization": f"Token {token}"} if token else {}
print(f"[*] Waiting for analysis to complete (max {max_wait}s)...")
elapsed = 0
while elapsed < max_wait:
try:
resp = requests.get(url, headers=headers, timeout=30)
resp.raise_for_status()
data = resp.json()
status = data.get("data", data.get("status", "unknown"))
if isinstance(status, dict):
status = status.get("status", "unknown")
if status in ("reported", "completed"):
print(f"[+] Analysis complete (status: {status})")
return True
if status in ("failed_analysis", "failed_processing"):
print(f"[!] Analysis failed: {status}", file=sys.stderr)
return False
print(f" Status: {status} ({elapsed}s elapsed)")
except requests.RequestException as e:
print(f" Connection error: {e}")
time.sleep(interval)
elapsed += interval
print("[!] Timed out waiting for analysis", file=sys.stderr)
return False
def get_report(server, token, task_id):
"""Retrieve the full analysis report for a completed task."""
url = f"{server}/apiv2/tasks/get/report/{task_id}/"
headers = {"Authorization": f"Token {token}"} if token else {}
resp = requests.get(url, headers=headers, timeout=120)
resp.raise_for_status()
return resp.json()
def extract_findings(report):
"""Extract structured findings from CAPE report."""
findings = []
# Signatures (behavioral detections)
for sig in report.get("signatures", []):
findings.append({
"category": "signature",
"name": sig.get("name", "Unknown"),
"severity": sig.get("severity", 0),
"description": sig.get("description", ""),
"families": sig.get("families", []),
"ttp": sig.get("ttp", {}),
})
# Network IOCs
network = report.get("network", {})
for dns_entry in network.get("dns", []):
findings.append({
"category": "network_dns",
"request": dns_entry.get("request", ""),
"type": dns_entry.get("type", ""),
"answers": [a.get("data", "") for a in dns_entry.get("answers", [])],
})
for http_entry in network.get("http", []):
findings.append({
"category": "network_http",
"method": http_entry.get("method", ""),
"uri": http_entry.get("uri", ""),
"host": http_entry.get("host", ""),
"port": http_entry.get("port", 80),
})
# Dropped files
for dropped in report.get("dropped", []):
findings.append({
"category": "dropped_file",
"name": dropped.get("name", ""),
"path": dropped.get("filepath", ""),
"type": dropped.get("type", ""),
"size": dropped.get("size", 0),
"sha256": dropped.get("sha256", ""),
})
# CAPE extracted payloads and configs
cape_data = report.get("CAPE", {})
if isinstance(cape_data, dict):
for cape_item in cape_data.get("payloads", []):
findings.append({
"category": "cape_payload",
"name": cape_item.get("name", ""),
"module": cape_item.get("module_path", ""),
"sha256": cape_item.get("sha256", ""),
"cape_type": cape_item.get("cape_type", ""),
})
for config in cape_data.get("configs", []):
findings.append({
"category": "cape_config",
"family": config.get("family", "unknown"),
"config_data": config,
})
return findings
def format_summary(report, findings):
"""Print human-readable analysis summary."""
info = report.get("info", {})
target = report.get("target", {})
score = report.get("malscore", info.get("score", 0))
print(f"\n{'='*60}")
print(f" CAPE Sandbox Analysis Report")
print(f"{'='*60}")
print(f" Task ID : {info.get('id', 'N/A')}")
print(f" Duration : {info.get('duration', 0)}s")
print(f" Malscore : {score}/10")
file_info = target.get("file", {})
if file_info:
print(f" File : {file_info.get('name', 'N/A')}")
print(f" SHA256 : {file_info.get('sha256', 'N/A')}")
print(f" Type : {file_info.get('type', 'N/A')}")
sig_findings = [f for f in findings if f["category"] == "signature"]
net_dns = [f for f in findings if f["category"] == "network_dns"]
net_http = [f for f in findings if f["category"] == "network_http"]
dropped = [f for f in findings if f["category"] == "dropped_file"]
configs = [f for f in findings if f["category"] == "cape_config"]
print(f"\n Signatures : {len(sig_findings)}")
print(f" DNS Queries : {len(net_dns)}")
print(f" HTTP Reqs : {len(net_http)}")
print(f" Dropped : {len(dropped)}")
print(f" CAPE Configs: {len(configs)}")
if sig_findings:
print(f"\n Top Signatures:")
for s in sorted(sig_findings, key=lambda x: x.get("severity", 0), reverse=True)[:10]:
sev = s.get("severity", 0)
label = "HIGH" if sev >= 3 else "MEDIUM" if sev >= 2 else "LOW"
print(f" [{label:6s}] {s['name']}: {s['description'][:80]}")
if configs:
print(f"\n Extracted Configs:")
for c in configs:
print(f" Family: {c.get('family', 'unknown')}")
return score
def main():
parser = argparse.ArgumentParser(
description="CAPE Sandbox malware analysis agent"
)
group = parser.add_mutually_exclusive_group(required=True)
group.add_argument("--file", help="Path to malware sample to submit")
group.add_argument("--url", help="URL to submit for analysis")
group.add_argument("--task-id", type=int, help="Retrieve report for existing task")
parser.add_argument("--output", "-o", help="Output JSON report path")
parser.add_argument("--server", help="CAPE server URL (or set CAPE_URL env var)")
parser.add_argument("--token", help="API token (or set CAPE_API_TOKEN env var)")
parser.add_argument("--machine", help="Specific VM to use for analysis")
parser.add_argument("--timeout", type=int, default=5, help="Analysis timeout in minutes")
parser.add_argument("--wait", type=int, default=600, help="Max seconds to wait for completion")
parser.add_argument("--verbose", "-v", action="store_true")
args = parser.parse_args()
if args.server:
os.environ["CAPE_URL"] = args.server
if args.token:
os.environ["CAPE_API_TOKEN"] = args.token
server, token = get_cape_config()
if args.task_id:
task_id = args.task_id
elif args.file:
task_id = submit_file(server, token, args.file, args.timeout, args.machine)
else:
task_id = submit_url(server, token, args.url, args.timeout)
if not args.task_id:
if not poll_task_status(server, token, task_id, args.wait):
sys.exit(1)
report = get_report(server, token, task_id)
findings = extract_findings(report)
score = format_summary(report, findings)
output_report = {
"timestamp": datetime.now(timezone.utc).isoformat(),
"tool": "CAPE Sandbox",
"task_id": task_id,
"malscore": score,
"findings_count": len(findings),
"findings": findings,
"risk_level": (
"CRITICAL" if score >= 8
else "HIGH" if score >= 5
else "MEDIUM" if score >= 3
else "LOW"
),
}
if args.output:
with open(args.output, "w") as f:
json.dump(output_report, f, indent=2)
print(f"\n[+] Report saved to {args.output}")
elif args.verbose:
print(json.dumps(output_report, indent=2))
if __name__ == "__main__":
main()