Security OSINT

Overview

Monitor Twitter/X and Reddit for security-related discussions — CVE mentions, zero-day chatter, breach reports, exploit code sharing, and emerging threats. Provides early warning intelligence often 24-48 hours before formal advisories.

When to Use

Activate when the user asks:

• "Find discussions about [CVE-XXXX-XXXXX] on Twitter"
• "What's the security community saying about [VULNERABILITY]?"
• "Monitor social media for [SOFTWARE] vulnerabilities"
• "OSINT research on [THREAT ACTOR/CAMPAIGN]"
• "Are there breach reports about [COMPANY] on social media?"
• "Threat intelligence from Twitter and Reddit"

Setup & Authentication

Before fetching data, ensure Xpoz access is configured. Follow these checks in order.

Check 1: Already authenticated?

If you have MCP tools, try calling any Xpoz tool (e.g.,

checkAccessKeyStatus

If you have the SDK, try:

from xpoz import XpozClient
client = XpozClient()  # reads XPOZ_API_KEY env var

If this succeeds without error → skip to Step 1.

If neither works, you need to authenticate. Choose the path that fits your environment:

Path A: MCP via mcporter (OpenClaw agents)

If

mcporter

mcporter call xpoz.checkAccessKeyStatus

If

hasAccessKey: true

mcporter config add xpoz https://mcp.xpoz.ai/mcp --auth oauth

Then authenticate — generate the OAuth URL and send it to the user:

Step 1: Generate authorization URL

import secrets, hashlib, base64, urllib.parse, json, urllib.request, os

verifier = secrets.token_urlsafe(64)
challenge = base64.urlsafe_b64encode(hashlib.sha256(verifier.encode()).digest()).rstrip(b'=').decode()
state = secrets.token_urlsafe(32)

# Dynamic client registration
reg_req = urllib.request.Request(
    'https://mcp.xpoz.ai/oauth/register',
    data=json.dumps({
        'client_name': 'Agent Skills',
        'redirect_uris': ['https://www.xpoz.ai/oauth/openclaw'],
        'grant_types': ['authorization_code'],
        'response_types': ['code'],
        'token_endpoint_auth_method': 'none',
    }).encode(),
    headers={'Content-Type': 'application/json'},
)
reg_resp = json.loads(urllib.request.urlopen(reg_req).read())

params = urllib.parse.urlencode({
    'response_type': 'code',
    'client_id': reg_resp['client_id'],
    'code_challenge': challenge,
    'code_challenge_method': 'S256',
    'redirect_uri': 'https://www.xpoz.ai/oauth/openclaw',
    'state': state,
    'scope': 'mcp:tools',
    'resource': 'https://mcp.xpoz.ai/',
})

auth_url = 'https://mcp.xpoz.ai/oauth/authorize?' + params

# Save state for token exchange
os.makedirs(os.path.expanduser('~/.cache/xpoz-oauth'), exist_ok=True)
with open(os.path.expanduser('~/.cache/xpoz-oauth/state.json'), 'w') as f:
    json.dump({'verifier': verifier, 'state': state, 'client_id': reg_resp['client_id'],
               'redirect_uri': 'https://www.xpoz.ai/oauth/openclaw'}, f)

print(auth_url)

Step 2: Send the URL to the user

Tell them:

"I need to connect to Xpoz for social media data. Please open this link and sign in:

[auth_url]

After authorizing, you'll see a code. Paste it back to me here."

Step 3: WAIT for the user to reply with the code. Do not proceed until they respond.

Step 4: Exchange the code for a token

Once the user provides the code (either a raw code or a URL containing

?code=...

import json, urllib.request, urllib.parse, subprocess, os

with open(os.path.expanduser('~/.cache/xpoz-oauth/state.json')) as f:
    oauth = json.load(f)

code = "THE_CODE_FROM_USER"  # Extract from user's reply

data = urllib.parse.urlencode({
    'grant_type': 'authorization_code',
    'code': code,
    'redirect_uri': oauth['redirect_uri'],
    'client_id': oauth['client_id'],
    'code_verifier': oauth['verifier'],
}).encode()

req = urllib.request.Request(
    'https://mcp.xpoz.ai/oauth/token',
    data=data,
    headers={'Content-Type': 'application/x-www-form-urlencoded'},
)
resp = json.loads(urllib.request.urlopen(req).read())
token = resp['access_token']

# Configure mcporter with the token (token is never printed)
subprocess.run(['mcporter', 'config', 'remove', 'xpoz'], capture_output=True)
subprocess.run(['mcporter', 'config', 'add', 'xpoz', 'https://mcp.xpoz.ai/mcp',
                '--header', f'Authorization=Bearer {token}'], check=True)

# Clean up
os.remove(os.path.expanduser('~/.cache/xpoz-oauth/state.json'))
print("Xpoz configured successfully")

Step 5: Verify with

mcporter call xpoz.checkAccessKeyStatus

hasAccessKey: true

Path B: MCP via Claude Code config

For Claude Code users without mcporter, add to

~/.claude.json

{
  "mcpServers": {
    "xpoz": {
      "url": "https://mcp.xpoz.ai/mcp",
      "transport": "http-stream"
    }
  }
}

Claude Code handles OAuth automatically on first tool call — the user just needs to authorize in their browser when prompted.

Path C: SDK (Python or TypeScript)

Ask the user:

"I need a Xpoz API key to access social media data. Please go to https://xpoz.ai/get-token (it's free, no credit card needed) and paste the key back to me."

WAIT for the user to reply with the key. Then:

Python:

pip install xpoz

from xpoz import XpozClient
client = XpozClient("THE_KEY_FROM_USER")

TypeScript:

npm install @xpoz/xpoz

import { XpozClient } from "@xpoz/xpoz";
const client = new XpozClient({ apiKey: "THE_KEY_FROM_USER" });
await client.connect();

Or set the environment variable and use the default constructor:

export XPOZ_API_KEY=THE_KEY_FROM_USER

Auth Errors

AuthenticationError

Step-by-Step Instructions

Step 1: Parse the Request

Extract:

• Target: CVE ID, software name, company, threat actor, or general topic
• Scope: specific vulnerability vs broad monitoring
• Platforms (default: Twitter + Reddit — where security researchers are most active)
• Time period (default: last 7 days; use 24-48h for breaking threats)

Build targeted queries:

For a specific CVE:

"CVE-2026-1234" OR "CVE202612345"

For a software vulnerability:

("[SOFTWARE]" AND ("vulnerability" OR "vuln" OR "exploit" OR "RCE" OR "zero-day" OR "0day" OR "CVE"))

For breach monitoring:

("[COMPANY]" AND ("breach" OR "hacked" OR "leak" OR "data leak" OR "compromised" OR "ransomware"))

For threat actor tracking:

("[THREAT ACTOR]" OR "[KNOWN ALIASES]") AND ("attack" OR "campaign" OR "APT" OR "malware")

Step 2: Fetch Security Discussions

Via MCP

Twitter (security researchers are very active here):

Call getTwitterPostsByKeywords:
  query: "<security query>"
  fields: ["id", "text", "authorUsername", "createdAtDate", "likeCount", "retweetCount", "impressionCount"]
  startDate: "<7 days ago, YYYY-MM-DD>"
  endDate: "<today, YYYY-MM-DD>"
  language: "en"

Find security researchers discussing the topic:

Call getTwitterUsersByKeywords:
  query: "<security query>"
  fields: ["id", "username", "name", "description", "followersCount", "relevantTweetsCount", "relevantTweetsLikesSum", "verified"]
  startDate: "<7 days ago>"

Reddit (r/netsec, r/cybersecurity, r/hacking, etc.):

Call getRedditPostsByKeywords:
  query: "<security query>"
  fields: ["id", "title", "text", "authorUsername", "createdAtDate", "score", "numComments", "subreddit", "url"]
  startDate: "<7 days ago>"

CRITICAL: Poll

checkOperationStatus

operationId

Via Python SDK

from xpoz import XpozClient

client = XpozClient()

cve_id = "CVE-2026-1234"
query = f'"{cve_id}"'

# Twitter - security researcher chatter
twitter_posts = client.twitter.search_posts(
    query,
    start_date="2026-02-16",
    end_date="2026-02-23",
    fields=["id", "text", "author_username", "created_at_date", "like_count", "retweet_count", "impression_count"]
)

# Find researchers discussing it
researchers = client.twitter.get_users_by_keywords(
    query,
    start_date="2026-02-16",
    fields=["username", "name", "description", "followers_count", "relevant_tweets_count", "verified"]
)

# Reddit - deeper technical discussions
reddit_posts = client.reddit.search_posts(
    query,
    start_date="2026-02-16",
    fields=["id", "title", "text", "author_username", "created_at_date", "score", "num_comments", "subreddit", "url"]
)

print(f"Twitter: {twitter_posts.pagination.total_rows} posts")
print(f"Reddit: {reddit_posts.pagination.total_rows} posts")
print(f"Researchers: {researchers.pagination.total_rows} users")

# Export for analysis
twitter_csv = twitter_posts.export_csv()
reddit_csv = reddit_posts.export_csv()

client.close()

Via TypeScript SDK

import { XpozClient } from "@xpoz/xpoz";

const client = new XpozClient();
await client.connect();

const cveId = "CVE-2026-1234";

const twitterPosts = await client.twitter.searchPosts(`"${cveId}"`, {
  startDate: "2026-02-16",
  endDate: "2026-02-23",
  fields: ["id", "text", "authorUsername", "createdAtDate", "likeCount", "retweetCount"],
});

const redditPosts = await client.reddit.searchPosts(`"${cveId}"`, {
  startDate: "2026-02-16",
  fields: ["id", "title", "text", "score", "numComments", "subreddit"],
});

await client.close();

Step 3: Analyze Threat Intelligence

Timeline Reconstruction:

• Sort all posts chronologically
• Identify the first public mention (potential disclosure date)
• Track how discussion evolved (initial report → PoC → exploitation → patches)

Severity Assessment (from social signals):

Source Credibility:

• Verified security researchers (check bio for "security", "pentest", "CISO", "CVE")
• High follower count in security niche
• Posted from known security company accounts
• Cross-referenced across multiple independent sources

Key Information to Extract:

• Affected software/versions
• Attack vector (remote/local, authentication required?)
• Exploit availability (PoC published?)
• Patch status (fixed? workaround available?)
• Active exploitation reports
• IoCs (indicators of compromise) shared

Step 4: Generate Report

## Security Intelligence: [TARGET]
**Period:** [date range] | **Sources:** Twitter ([X] posts), Reddit ([X] posts)

### ⚠️ Threat Summary
**Severity:** Critical / High / Medium / Low
**Status:** [Active exploitation / PoC available / Discussion only / Patched]
**First seen:** [date of earliest social mention]

### Timeline
| Date | Source | Event |
|------|--------|-------|
| Feb 16 | Twitter @researcher | First public mention of vulnerability |
| Feb 17 | Reddit r/netsec | Technical analysis posted |
| Feb 18 | Twitter @vendor | Patch announced |

### Technical Details (from social sources)
- **Affected:** [software, versions]
- **Vector:** [remote/local, auth requirements]
- **Impact:** [RCE, data leak, DoS, etc.]
- **Exploit:** [PoC available? Where?]
- **Patch:** [Available? Version? Workaround?]

### Key Voices
| Researcher | Followers | Posts | Credibility |
|-----------|-----------|-------|-------------|
| @security_expert | 50K | 3 | High (CISO at [company]) |
| ... | ... | ... | ... |

### Notable Posts
> "Actual quote from security researcher" — @username (❤️ X, 🔁 X)

### Subreddit Activity
| Subreddit | Posts | Top Thread |
|-----------|-------|-----------|
| r/netsec | X | "Title..." (⬆️ X, 💬 X) |
| r/cybersecurity | X | "Title..." |

### Recommended Actions
1. [Immediate: patch/mitigate if affected]
2. [Monitor: watch for exploitation reports]
3. [Investigate: check logs for IoCs]

Example Prompts

• "What's the security community saying about CVE-2026-1234?"
• "Monitor Twitter for Log4Shell discussions in the last 48 hours"
• "OSINT: find breach reports about [Company] on social media"
• "Are there any zero-day discussions about Chrome this week?"
• "Track discussions about the latest ransomware campaign on Twitter and Reddit"
• "Find security researchers talking about MCP server vulnerabilities"

Notes

• Security discussions on Twitter often precede formal CVE publication by 24-48 hours
• Reddit r/netsec and r/cybersecurity provide technical depth; Twitter provides speed
• Use

  relevantTweetsCount

  from user search to find who's most actively discussing a threat
• Be careful with sensitive information — don't amplify exploit code or IoCs unnecessarily
• Free tier: 100K results/month at xpoz.ai