external/anthropic-cybersecurity-skills/skills/detecting-ransomware-precursors-in-network/SKILL.md
Detects early-stage ransomware indicators in network traffic before encryption begins, including initial access broker activity, command-and-control beaconing, credential harvesting, reconnaissance scanning, and staging behavior. Uses network detection tools (Zeek, Suricata, Arkime), SIEM correlation rules, and threat intelligence feeds to identify ransomware precursor patterns such as Cobalt Strike beacons, Mimikatz network signatures, and RDP brute-force attempts. Activates for requests involving pre-ransomware detection, network-based ransomware indicators, or early warning ransomware monitoring.
npx skillsauth add seikaikyo/dash-skills detecting-ransomware-precursors-in-networkInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Do not use for post-encryption response (see recovering-from-ransomware-attack). This skill focuses on the pre-encryption detection window where containment can prevent data loss.
Map network-observable indicators to each pre-encryption phase:
| Kill Chain Phase | Network Indicators | Detection Source | |------------------|--------------------|------------------| | Initial Access | RDP brute force, VPN credential stuffing, phishing callback | Firewall logs, IDS, proxy logs | | C2 Establishment | Cobalt Strike beacons (HTTPS/DNS), Sliver/Brute Ratel callbacks | Zeek SSL/HTTP logs, DNS logs | | Credential Harvesting | NTLM relay, Kerberoasting, DCSync traffic | Zeek Kerberos/NTLM logs, DC logs | | Reconnaissance | Internal port scanning, AD enumeration (LDAP/SMB) | Zeek conn.log, flow data | | Lateral Movement | PsExec/WMI/WinRM traffic, RDP pivoting, SMB file copies | Zeek SMB/DCE-RPC logs | | Staging | Data aggregation, archive creation, cloud upload prep | Proxy logs, DNS logs, DLP |
Suricata rules for common ransomware precursors:
# Cobalt Strike default HTTPS beacon profile detection
alert tls $HOME_NET any -> $EXTERNAL_NET any (msg:"RANSOMWARE PRECURSOR - Cobalt Strike Default TLS Certificate"; tls.cert_subject; content:"Major Cobalt Strike"; sid:3000001; rev:1;)
# Cobalt Strike DNS beacon
alert dns $HOME_NET any -> any 53 (msg:"RANSOMWARE PRECURSOR - Cobalt Strike DNS Beacon Pattern"; dns.query; pcre:"/^[a-z0-9]{3}\.[a-z]{4,8}\./"; threshold:type both, track by_src, count 50, seconds 60; sid:3000002; rev:1;)
# Mimikatz network signature (DCSync - DRS GetNCChanges)
alert tcp $HOME_NET any -> $HOME_NET 135 (msg:"RANSOMWARE PRECURSOR - Possible DCSync/Mimikatz"; content:"|05 00 0b|"; offset:0; depth:3; content:"|e3 51 4d 2b 4b 47 15 d2|"; sid:3000003; rev:1;)
# Internal network scanning (many connections, few bytes)
alert tcp $HOME_NET any -> $HOME_NET any (msg:"RANSOMWARE PRECURSOR - Internal Port Scan"; flags:S; threshold:type both, track by_src, count 100, seconds 10; sid:3000004; rev:1;)
# PsExec service installation over SMB
alert tcp $HOME_NET any -> $HOME_NET 445 (msg:"RANSOMWARE PRECURSOR - PsExec Service Install"; content:"|ff|SMB"; content:"PSEXESVC"; nocase; sid:3000005; rev:1;)
# RDP brute force from internal host (lateral movement)
alert tcp $HOME_NET any -> $HOME_NET 3389 (msg:"RANSOMWARE PRECURSOR - Internal RDP Brute Force"; flow:to_server,established; threshold:type both, track by_src, count 20, seconds 60; sid:3000006; rev:1;)
# Large SMB file transfer (data staging)
alert tcp $HOME_NET any -> $HOME_NET 445 (msg:"RANSOMWARE PRECURSOR - Large SMB Transfer Possible Staging"; flow:to_server,established; dsize:>60000; threshold:type both, track by_src, count 100, seconds 300; sid:3000007; rev:1;)
Zeek scripts for behavioral detection:
# detect_ransomware_precursors.zeek
# Detect high volume of failed SMB connections (credential testing)
@load base/protocols/smb
module RansomwarePrecursor;
export {
redef enum Notice::Type += {
SMB_Brute_Force,
Suspicious_Internal_Scan,
Excessive_DNS_Queries,
SMB_Admin_Share_Access,
};
const smb_fail_threshold = 10 &redef;
const scan_threshold = 50 &redef;
const dns_query_threshold = 200 &redef;
}
global smb_fail_count: table[addr] of count &default=0 &create_expire=5min;
global conn_count: table[addr] of set[addr] &create_expire=1min;
event smb2_message(c: connection, hdr: SMB2::Header, is_orig: bool) {
if (hdr$status != 0) {
++smb_fail_count[c$id$orig_h];
if (smb_fail_count[c$id$orig_h] >= smb_fail_threshold) {
NOTICE([$note=SMB_Brute_Force,
$msg=fmt("Host %s has %d failed SMB attempts", c$id$orig_h, smb_fail_count[c$id$orig_h]),
$src=c$id$orig_h,
$identifier=cat(c$id$orig_h)]);
}
}
}
event new_connection(c: connection) {
if (c$id$orig_h in Site::local_nets && c$id$resp_h in Site::local_nets) {
if (c$id$orig_h !in conn_count)
conn_count[c$id$orig_h] = set();
add conn_count[c$id$orig_h][c$id$resp_h];
if (|conn_count[c$id$orig_h]| >= scan_threshold) {
NOTICE([$note=Suspicious_Internal_Scan,
$msg=fmt("Host %s connected to %d internal hosts in 1 min", c$id$orig_h, |conn_count[c$id$orig_h]|),
$src=c$id$orig_h,
$identifier=cat(c$id$orig_h)]);
}
}
}
Splunk correlation for ransomware precursor chain:
| tstats count FROM datamodel=Network_Traffic
WHERE earliest=-24h All_Traffic.dest_port IN (445, 135, 139, 3389, 5985, 5986)
AND All_Traffic.src_ip IN 10.0.0.0/8
AND All_Traffic.dest_ip IN 10.0.0.0/8
BY All_Traffic.src_ip, All_Traffic.dest_port, _time span=1h
| stats dc(All_Traffic.dest_port) as port_count,
values(All_Traffic.dest_port) as ports,
count as total_conns
BY All_Traffic.src_ip
| where port_count >= 3 AND total_conns > 50
| rename All_Traffic.src_ip as src_ip
| lookup threat_intel_ioc ip as src_ip OUTPUT threat_type
| eval risk_score = case(
port_count >= 5 AND total_conns > 200, "CRITICAL",
port_count >= 3 AND total_conns > 50, "HIGH",
1=1, "MEDIUM")
| table src_ip, ports, port_count, total_conns, risk_score, threat_type
Microsoft Sentinel KQL - Ransomware precursor correlation:
let timeframe = 24h;
let RDPBruteForce = SecurityEvent
| where TimeGenerated > ago(timeframe)
| where EventID == 4625
| where LogonType == 10
| summarize FailedRDP = count() by TargetAccount, IpAddress, bin(TimeGenerated, 1h)
| where FailedRDP > 10;
let SuspiciousSMB = SecurityEvent
| where TimeGenerated > ago(timeframe)
| where EventID == 5145
| where ShareName has "ADMIN$" or ShareName has "C$" or ShareName has "IPC$"
| summarize AdminShareAccess = count() by SubjectUserName, IpAddress, bin(TimeGenerated, 1h)
| where AdminShareAccess > 5;
let ServiceInstalls = SecurityEvent
| where TimeGenerated > ago(timeframe)
| where EventID == 7045
| where ServiceName has_any ("PSEXESVC", "meterpreter", "beacon");
RDPBruteForce
| join kind=inner SuspiciousSMB on IpAddress
| project TimeGenerated, IpAddress, TargetAccount, FailedRDP, SubjectUserName, AdminShareAccess
| extend AlertTitle = "Ransomware Precursor: RDP Brute Force + Admin Share Access"
Configure automated IOC feeds for known ransomware infrastructure:
# Download and update ransomware C2 blocklists
# abuse.ch Feodo Tracker (Cobalt Strike, TrickBot, BazarLoader C2s)
curl -s https://feodotracker.abuse.ch/downloads/ipblocklist.csv | \
grep -v "^#" | cut -d, -f2 > /opt/threat-intel/feodo_ips.txt
# abuse.ch URLhaus (malware distribution URLs)
curl -s https://urlhaus.abuse.ch/downloads/csv_recent/ | \
grep -v "^#" | cut -d, -f3 > /opt/threat-intel/urlhaus_urls.txt
# abuse.ch ThreatFox (ransomware IOCs)
curl -s https://threatfox.abuse.ch/export/csv/recent/ | \
grep -i "ransomware" | cut -d, -f3 > /opt/threat-intel/ransomware_iocs.txt
# CISA Known Exploited Vulnerabilities (initial access vectors)
curl -s https://www.cisa.gov/sites/default/files/feeds/known_exploited_vulnerabilities.json | \
python3 -c "import json,sys; data=json.load(sys.stdin); [print(v['cveID'],v['vendorProject'],v['product']) for v in data['vulnerabilities'] if 'ransomware' in v.get('knownRansomwareCampaignUse','').lower()]"
Define triage procedures based on precursor confidence level:
| Alert Type | Confidence | Response Time | Action | |------------|-----------|---------------|--------| | Confirmed Cobalt Strike beacon | High | 15 minutes | Isolate host immediately, trigger IR | | DCSync/Kerberoasting from non-DC | High | 15 minutes | Disable account, isolate host, trigger IR | | Internal port scan + admin share access | Medium-High | 30 minutes | Investigate source host, check EDR telemetry | | RDP brute force from internal host | Medium | 1 hour | Verify if legitimate admin activity, check host | | Unusual DNS query volume | Low-Medium | 4 hours | Check for DNS tunneling, correlate with other alerts |
| Term | Definition | |------|------------| | Ransomware Precursor | Network activity that precedes ransomware encryption, including C2 communication, lateral movement, and data staging | | Dwell Time | Time between initial compromise and ransomware deployment, averaging 21 days but sometimes as short as 17 minutes | | Initial Access Broker (IAB) | Threat actors who sell compromised network access to ransomware operators on dark web markets | | Beaconing | Periodic C2 callbacks from implants (Cobalt Strike, Sliver) that can be detected by analyzing connection timing patterns | | Kerberoasting | Credential harvesting technique requesting Kerberos service tickets for offline cracking, detectable via unusual TGS-REQ patterns | | DCSync | Technique using Directory Replication Service to extract password hashes from domain controllers, critical ransomware precursor |
Context: A manufacturing company's SOC receives an alert for unusual SMB traffic from a workstation (10.1.5.42) in the engineering department. The workstation connected to 47 internal hosts on port 445 within 5 minutes at 2:00 AM.
Approach:
Pitfalls:
## Ransomware Precursor Detection Alert
**Alert ID**: [SIEM-generated ID]
**Detection Time**: [Timestamp]
**Source Host**: [IP / Hostname]
**Confidence**: [High / Medium / Low]
**Kill Chain Phase**: [Initial Access / C2 / Credential Harvest / Recon / Lateral Movement / Staging]
### Indicators Detected
| Indicator | Source | Detail | MITRE ATT&CK |
|-----------|--------|--------|--------------|
| [Type] | [Zeek/Suricata/SIEM] | [Description] | [T-ID] |
### Correlation Chain
1. [Timestamp] - [Event 1]
2. [Timestamp] - [Event 2]
3. [Timestamp] - [Event 3]
### Recommended Actions
- [ ] Isolate source host from network
- [ ] Check EDR telemetry for host-based indicators
- [ ] Reset credentials for affected user accounts
- [ ] Block identified C2 infrastructure
- [ ] Escalate to incident response team
tools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.