
Detecting Ransomware Precursors
FreeIdentify early-stage ransomware indicators in network traffic.
Free · Opens the source repo
What Detecting Ransomware Precursors does
This skill focuses on detecting early-stage ransomware indicators within network traffic before encryption occurs. By monitoring for specific behaviors associated with ransomware deployment, such as initial access broker activity and command-and-control beaconing, this tool helps security teams mitigate potential threats before they escalate. It utilizes network detection tools like Zeek, Suricata, and Arkime, combined with threat intelligence feeds, to identify patterns indicative of ransomware precursor activities.
The skill is designed for security professionals and incident response teams who need to build effective detection rules for pre-ransomware network activity. Given that the average time from Cobalt Strike deployment to encryption is just 17 minutes, having a proactive detection mechanism is crucial. This skill aids in creating SIEM correlation rules that can chain multiple precursor events into high-confidence alerts, allowing for timely responses to potential threats.
Users can leverage this skill to tune their network detection systems, ensuring they can distinguish between normal administrative activities and potential ransomware staging behaviors. By mapping observable indicators to the ransomware kill chain phases, security teams can better understand and respond to threats as they emerge. This skill is particularly useful for organizations looking to enhance their network security posture against ransomware attacks.
However, it is important to note that this skill is not intended for post-encryption response scenarios. It specifically targets the pre-encryption detection window, making it unsuitable for recovery efforts after a ransomware attack has already occurred.
When to use it
Use this skill when building detection rules for pre-ransomware network activity or monitoring for indicators of initial access brokers.
When not to use it
Do not use this skill for post-encryption response efforts, as it focuses solely on pre-encryption detection.
What you can build with it
Building Detection Rules
Create effective detection rules for pre-ransomware network activity to enhance your security posture.
Monitoring Initial Access Indicators
Continuously monitor for indicators of initial access broker activity to catch potential threats early.
Creating SIEM Correlation Rules
Develop correlation rules that link multiple precursor events into actionable alerts for incident response.
How to install Detecting Ransomware Precursors
View source1. Install with the skills CLI
npx skills add mukul975/anthropic-cybersecurity-skills/detecting-ransomware-precursors-in-network --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by mukul975Detecting Ransomware Precursors in Network Traffic
When to Use
- Building detection rules for pre-ransomware network activity (the average time from Cobalt Strike deployment to encryption is 17 minutes)
- Monitoring for initial access broker (IAB) indicators that precede ransomware deployment
- Creating SIEM correlation rules that chain multiple precursor events into high-confidence alerts
- Tuning network detection systems to distinguish ransomware staging from normal administrative activity
- Investigating suspicious network patterns that may indicate ransomware operators have established a foothold
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.
Prerequisites
- Network detection platform (Zeek/Bro, Suricata, or Arkime/Moloch) deployed on network TAP or SPAN ports
- SIEM platform (Splunk, Elastic Security, Microsoft Sentinel, or QRadar) ingesting network logs
- Threat intelligence feeds covering ransomware IOCs (CISA, abuse.ch, OTX, MISP)
- Network flow data (NetFlow/IPFIX) from core routers and firewalls
- DNS query logging from internal resolvers
- Full packet capture capability for incident investigation
Workflow
Step 1: Identify Ransomware Kill Chain Phases in Network Traffic
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 |
Step 2: Deploy Network Detection Rules
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$orig_h)]);
}
}
}
Step 3: Create SIEM Correlation Rules
Splunk correlation for ransomware precursor chain:
| tstats count FROM datamodel=Network_Traffic
WHERE earliest=-24h All_Traffic.dest_port IN (445, 135, 139, 3389, 5985, 5986)
AND All_Traffic.src_ip IN 10.0.0.0/8
AND All_Traffic.dest_ip IN 10.0.0.0/8
BY All_Traffic.src_ip, All_Traffic.dest_port, _time span=1h
| stats dc(All_Traffic.dest_port) as port_count,
values(All_Traffic.dest_port) as ports,
count as total_conns
BY All_Traffic.src_ip
| where port_count >= 3 AND total_conns > 50
| rename All_Traffic.src_ip as src_ip
| lookup threat_intel_ioc ip as src_ip OUTPUT threat_type
| eval risk_score = case(
port_count >= 5 AND total_conns > 200, "CRITICAL",
port_count >= 3 AND total_conns > 50, "HIGH",
1=1, "MEDIUM")
| table src_ip, ports, port_count, total_conns, risk_score, threat_type
Microsoft Sentinel KQL - Ransomware precursor correlation:
let timeframe = 24h;
let RDPBruteForce = SecurityEvent
| where TimeGenerated > ago(timeframe)
| where EventID == 4625
| where LogonType == 10
| summarize FailedRDP = count() by TargetAccount, IpAddress, bin(TimeGenerated, 1h)
| where FailedRDP > 10;
let SuspiciousSMB = SecurityEvent
| where TimeGenerated > ago(timeframe)
| where EventID == 5145
| where ShareName has "ADMIN$" 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"
Step 4: Integrate Threat Intelligence
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()]"
Step 5: Establish Alert Triage and Escalation
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 |
Key Concepts
| 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 |
Tools & Systems
- Zeek (formerly Bro): Network analysis framework generating structured logs for SMB, Kerberos, DNS, HTTP, and TLS connections
- Suricata: High-performance IDS/IPS with protocol analysis and multi-threading support for ransomware signature detection
- Arkime (formerly Moloch): Full packet capture and search platform for deep forensic investigation of network events
- RITA (Real Intelligence Threat Analytics): Open-source tool for detecting beaconing, DNS tunneling, and long connections in Zeek logs
- AC-Hunter: Network threat hunting platform from Active Countermeasures for beacon detection and C2 identification
Common Scenarios
Scenario: Detecting LockBit Precursors in a Manufacturing Network
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:
- Zeek conn.log analysis shows 10.1.5.42 initiated connections to 47 unique internal IPs on port 445, 135, and 3389 between 01:55-02:05
- Zeek ssl.log reveals an outbound HTTPS connection to 185.x.x.x every 60 seconds with consistent 48-byte payloads (Cobalt Strike beacon pattern)
- RITA beacon analysis confirms high beacon score (0.96) for the external IP with 60-second jitter
- Zeek kerberos.log shows TGS-REQ for multiple SPN accounts from 10.1.5.42 (Kerberoasting)
- SMB tree_connect events show access to ADMIN$ shares on 12 hosts (lateral movement staging)
- Containment: Host isolated, credentials for engineering user reset, blocking rule for C2 IP deployed
- Full IR initiated before ransomware deployment could begin
Pitfalls:
- Dismissing internal port scans as vulnerability scanner activity without verifying the source is an authorized scanner
- Not correlating individual low-severity alerts (DNS anomaly + SMB access + failed logins) into a high-severity chain
- Setting detection thresholds too high to avoid false positives, missing low-and-slow reconnaissance
- Ignoring encrypted traffic analysis (JA3/JA4 fingerprinting) that can identify Cobalt Strike even in TLS tunnels
Output Format
## 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
Frequently asked questions about Detecting Ransomware Precursors
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