LogZilla

Introduction to the OWASP Top 10

The Open Web Application Security Project (OWASP) is a nonprofit organization focused on improving the security of software. The OWASP Top 10 represents the most critical security risks to web applications, based on comprehensive data analysis and industry consensus. This list helps developers, security professionals, and organizations understand and address the most common web application vulnerabilities. Learn more about the OWASP Top 10.

The OWASP Top 10 is a list of the most critical security risks to web applications.

The OWASP Top 10 2021 Complete List

A01:2021 – Broken Access Control
A02:2021 – Cryptographic Failures
A03:2021 – Injection
A04:2021 – Insecure Design
A05:2021 – Security Misconfiguration
A06:2021 – Vulnerable and Outdated Components
A07:2021 – Identification and Authentication Failures
A08:2021 – Software and Data Integrity Failures
A09:2021 – Security Logging and Monitoring Failures
A10:2021 – Server-Side Request Forgery (SSRF)

Why Log Management is Critical for OWASP Top 10 Defense

Effective log management serves as both a detective control and a foundation for incident response across all OWASP Top 10 vulnerabilities. While secure coding practices prevent these vulnerabilities, comprehensive logging enables organizations to:

Detect exploitation attempts in real-time
Track attack patterns and threat actor behavior
Measure security control effectiveness
Enable rapid incident response and forensic analysis
Meet compliance requirements for security monitoring

LogZilla's approach transforms traditional reactive logging into proactive security intelligence through real-time analysis, intelligent preprocessing, and automated response capabilities.

LogZilla's Approach to OWASP Top 10 Detection

LogZilla transforms raw log messages into structured, searchable data using user tags—custom metadata fields extracted via parsing rules. Syslog protocol with structured data is standardized in RFC 5424, providing a foundation for consistent log message formatting. This approach provides immediate visibility into security patterns without complex queries.

Micro-FAQ

What is the OWASP Top 10?

The OWASP Top 10 is a list of the most critical security risks to web applications.

Which logs help detect OWASP Top 10 issues?

Application access logs, authentication logs, WAF events, and API gateway logs provide coverage when fields are normalized and retained.

Should logs be JSON?

JSON is not required, but consistent parsing and schema validation improve detection and troubleshooting.

Which transport should be used for app logs?

Use TCP/TLS for reliability and confidentiality; UDP is acceptable for constrained sources when loss is tolerable.

Summary

LogZilla provides comprehensive OWASP Top 10 detection capabilities through intelligent log parsing, real-time analysis, and automated response. The platform's user tag system transforms raw log messages into structured, searchable data, enabling immediate visibility into security patterns without complex queries.

A01:2021 – Broken Access Control

What it is: Users acting outside of their intended permissions, accessing unauthorized functionality or data.

LogZilla Detection Strategy:

yaml
# /etc/logzilla/rules.d/100-access-control.yaml
rewrite_rules:
  - comment: "Detect unauthorized access attempts"
    match:
      field: "message"
      op: "=~"
      value: "(?:access denied|unauthorized|forbidden|privilege|escalation)"
    tag:
      security_event: "access_control_violation"
      risk_level: "high"
  - comment: "Track privilege escalation"
    match:
      field: "message"
      op: "=~"
      value: "user ([^\\s]+) attempted (?:admin|root|sudo) access"
    tag:
      privilege_escalation_user: "$1"
      security_event: "privilege_escalation"

LogZilla UI Monitoring:

Widget: TopN users with access violations (privilege_escalation_user)
Alert: Real-time notifications for security_event:privilege_escalation
Dashboard: Access control violation trends over time

A02:2021 – Cryptographic Failures

What it is: Failures related to cryptography that lead to sensitive data exposure.

LogZilla Detection Strategy:

lua
-- /etc/logzilla/rules.d/200-crypto-failures.lua
function process(event)
    local message = event.message
    
    -- Detect weak crypto usage
    if string.match(message, "SSL.*TLS.*1%.[01]") or
       string.match(message, "MD5") or
       string.match(message, "SHA1") or
       string.match(message, "DES") then
        event.user_tags.crypto_weakness = "deprecated_algorithm"
        event.user_tags.security_event = "crypto_failure"
    end
    
    -- Detect certificate issues
    if string.match(message, "certificate.*expired") or
       string.match(message, "certificate.*invalid") then
        event.user_tags.cert_issue = "invalid_certificate"
        event.user_tags.security_event = "crypto_failure"
    end
end

LogZilla Response:

Immediate Alert: Certificate expiration warnings
Compliance Dashboard: Weak cryptography usage tracking
Automated Action: Generate security team tickets for crypto failures

A03:2021 – Injection

What it is: SQL injection, NoSQL injection, OS command injection, and other injection flaws.

LogZilla Detection Strategy:

yaml
# /etc/logzilla/rules.d/300-injection-detection.yaml
rewrite_rules:
  - comment: "SQL Injection Detection"
    match:
      field: "message"
      op: "=~"
      value: "(?i)(union.*select|or.*1=1|drop.*table|exec.*xp_|script.*alert)"
    tag:
      attack_type: "injection"
      injection_type: "sql"
      threat_level: "critical"
  - comment: "Command Injection Detection"
    match:
      field: "message"
      op: "=~"
      value: "(?:;|\\||&|`|\\$\\(|\\${).*(?:rm|cat|ls|wget|curl|nc|bash)"
    tag:
      attack_type: "injection"
      injection_type: "command"
      threat_level: "critical"

LogZilla UI Searches:

text
attack_type:injection AND threat_level:critical
injection_type:sql
injection_type:command

A04:2021 – Insecure Design

What it is: Design flaws that cannot be fixed by implementation alone.

LogZilla Detection Strategy:

lua
-- /etc/logzilla/rules.d/400-insecure-design.lua
function process(event)
    local message = event.message
    
    -- Detect business logic bypasses
    if string.match(message, "price.*modified") or
       string.match(message, "quantity.*negative") or
       string.match(message, "discount.*100%") then
        event.user_tags.business_logic_bypass = "detected"
        event.user_tags.security_event = "insecure_design"
    end
    
    -- Detect workflow violations
    if string.match(message, "step.*skipped") or
       string.match(message, "validation.*bypassed") then
        event.user_tags.workflow_violation = "detected"
        event.user_tags.security_event = "insecure_design"
    end
end

A05:2021 – Security Misconfiguration

What it is: Insecure default configurations, incomplete configurations, or misconfigured HTTP headers.

LogZilla Detection Strategy:

yaml
# /etc/logzilla/rules.d/500-misconfig-detection.yaml
rewrite_rules:
  - comment: "Default credentials usage"
    match:
      field: "message"
      op: "=~"
      value: "(?:admin:admin|root:root|admin:password|default.*credentials)"
    tag:
      security_event: "default_credentials"
      config_issue: "weak_auth"
  - comment: "Debug mode in production"
    match:
      field: "message"
      op: "=~"
      value: "(?:debug.*enabled|stack.*trace|error.*details)"
    tag:
      security_event: "debug_enabled"
      config_issue: "information_disclosure"

A06:2021 – Vulnerable and Outdated Components

What it is: Using components with known vulnerabilities.

LogZilla Detection Strategy:

lua
-- /etc/logzilla/rules.d/600-vulnerable-components.lua
function process(event)
    local message = event.message
    
    -- Track component versions
    local version = string.match(message, "([^\\s]+)\\s+version\\s+([0-9\\.]+)")
    if version then
        event.user_tags.component_name = version
        event.user_tags.component_version = string.match(message, "version\\s+([0-9\\.]+)")
    end
    
    -- Detect known vulnerable patterns
    if string.match(message, "log4j.*2\\.[0-9]") or
       string.match(message, "struts.*2\\.[0-5]") then
        event.user_tags.vulnerable_component = "detected"
        event.user_tags.security_event = "vulnerable_component"
    end
end

A07:2021 – Identification and Authentication Failures

What it is: Broken authentication and session management.

LogZilla Detection Strategy:

yaml
# /etc/logzilla/rules.d/700-auth-failures.yaml
rewrite_rules:
  - comment: "Authentication failures"
    match:
      field: "message"
      op: "=~"
      value: "(?:login.*failed|authentication.*failed|invalid.*credentials)"
    tag:
      auth_event: "failure"
      security_event: "auth_failure"
  - comment: "Session hijacking indicators"
    match:
      field: "message"
      op: "=~"
      value: "(?:session.*hijacked|token.*stolen|concurrent.*sessions)"
    tag:
      auth_event: "session_attack"
      security_event: "session_hijacking"

LogZilla Correlation Rules:

Brute Force: >10 auth failures from same IP in 5 minutes
Credential Stuffing: Multiple usernames from same IP
Session Anomalies: Concurrent sessions from different locations

A08:2021 – Software and Data Integrity Failures

What it is: Code and infrastructure that do not protect against integrity violations.

LogZilla Detection Strategy:

lua
-- /etc/logzilla/rules.d/800-integrity-failures.lua
function process(event)
    local message = event.message
    
    -- Detect checksum failures
    if string.match(message, "checksum.*mismatch") or
       string.match(message, "hash.*verification.*failed") then
        event.user_tags.integrity_failure = "checksum_mismatch"
        event.user_tags.security_event = "integrity_violation"
    end
    
    -- Detect unsigned code execution
    if string.match(message, "unsigned.*code") or
       string.match(message, "certificate.*verification.*failed") then
        event.user_tags.integrity_failure = "unsigned_code"
        event.user_tags.security_event = "integrity_violation"
    end
end

A09:2021 – Security Logging and Monitoring Failures

What LogZilla Solves: This is precisely what LogZilla prevents through:

Real-time Processing: ~5M EPS with immediate-first deduplication
Comprehensive Coverage: All log sources with structured parsing
Intelligent Alerting: Context-aware triggers with correlation
Audit Trail: Complete forensic capabilities with archive search
Compliance: Automated reporting and retention management

LogZilla Monitoring Health:

yaml
# /etc/logzilla/rules.d/900-monitoring-health.yaml
rewrite_rules:
  - comment: "Log ingestion monitoring"
    match:
      field: "program"
      op: "eq"
      value: "logzilla"
    tag:
      system_health: "log_ingestion"
      monitoring_status: "active"

A10:2021 – Server-Side Request Forgery (SSRF)

What it is: Web applications fetching remote resources without validating user-supplied URLs.

LogZilla Detection Strategy:

yaml
# /etc/logzilla/rules.d/1000-ssrf-detection.yaml
rewrite_rules:
  - comment: "SSRF attempt detection"
    match:
      field: "message"
      op: "=~"
      value: "(?:localhost|127\\.0\\.0\\.1|169\\.254|10\\.|192\\.168|172\\.1[6-9]|172\\.2[0-9]|172\\.3[01])"
    tag:
      attack_type: "ssrf"
      target_type: "internal_network"
      threat_level: "high"
  - comment: "Cloud metadata SSRF"
    match:
      field: "message"
      op: "=~"
      value: "169\\.254\\.169\\.254"
    tag:
      attack_type: "ssrf"
      target_type: "cloud_metadata"
      threat_level: "critical"

Using the LogZilla UI for Security Analysis

Once user tags are configured, the LogZilla UI provides powerful, intuitive analysis capabilities:

Dashboard Widgets for Security Monitoring

Top Failed Login Users:

Widget Type: TopN
Field: auth_fail_user
Filter: auth_status:failed

Authentication Failure Rate Over Time:

Widget Type: EventRate
Filter: auth_status:failed

Top Attacking IP Addresses:

Widget Type: TopN
Field: attacker_ip

Latest Critical Security Events:

Widget Type: Search
Filter: attack_type:SQLi OR path_traversal_attempts:>2

Simple UI Searches

With user tags configured, security searches become straightforward:

All failed authentications:

text
auth_status:failed

Brute force attempts (multiple failures from same IP):

text
auth_fail_source:203.0.113.5 AND auth_status:failed

All injection attacks:

text
attack_type:SQLi

Severe path traversal attempts:

text
path_traversal_attempts:>3

Combined security events:

text
attack_type:SQLi OR attack_type:path_traversal OR auth_status:failed

Automated Security Response with Triggers

LogZilla Triggers enable automated responses to security events:

Brute Force Detection

Trigger Configuration:

Condition: auth_status:failed
Rule Type: SingleWithThreshold
Threshold: More than 10 events in 1 minute from same auth_fail_source
Action: Execute script to add IP to firewall blocklist

Critical Injection Alert

Trigger Configuration:

Condition: attack_type:SQLi
Action: Send email to security team with attacker_ip and attack_payload

Path Traversal Response

Trigger Configuration:

Condition: path_traversal_attempts:>2
Action: Create high-priority notification for immediate investigation

Advanced Correlation for Complex Attacks

For multi-stage attacks, LogZilla's Event Correlation engine tracks patterns across multiple events:

Example: Detect port scanning followed by login attempts

Stage 1: High connection rate from single IP
Stage 2: Authentication attempts from same IP within time window
Response: Automated blocking with security team notification

When to Use API vs UI

Use the UI for:

Interactive security investigations
Real-time monitoring dashboards
Manual incident response
Exploring attack patterns

Use the API for:

Automated threat hunting scripts
Integration with SOAR platforms
Scheduled security reports
Custom security applications

Example API Query (for automation):

json
{
  "type": "TopN",
  "params": {
    "time_range": {"preset": "last_1_hours"},
    "field": "attacker_ip",
    "filter": [
      {"field": "attack_type", "value": "SQLi"}
    ],
    "limit": 20
  }
}

For upstream controls that reduce noise before analysis, see Cloud SIEM cost‑control approaches and Syslog Essentials. Organizations implementing comprehensive security monitoring should also review advanced event deduplication strategies to optimize detection accuracy while reducing alert fatigue.

AI-Powered OWASP Detection

LogZilla AI Copilot enhances OWASP Top 10 detection through natural language analysis:

AI Query Examples for OWASP Detection

OWASP Category	AI Query
A01: Broken Access Control	"Show unauthorized access attempts in the last hour"
A03: Injection	"Identify SQL injection and XSS attempts across all web servers"
A07: Auth Failures	"Analyze authentication failures and identify brute force attacks"
A09: Logging Failures	"Check for gaps in security logging coverage"
A10: SSRF	"Detect server-side request forgery attempts"

Real-World AI Analysis Example

Scenario: Suspected injection attack

AI Query: "Analyze web application logs from the last 4 hours. Identify injection attempts, correlate attack patterns, map to MITRE ATT&CK, and provide WAF rules to block attackers."

AI Response includes:

Attack summary with severity rankings
Source IP addresses with geolocation
Injection payloads detected (SQLi, XSS, command injection)
MITRE ATT&CK techniques (T1190, T1059)
WAF rules for ModSecurity, AWS WAF, and Cloudflare
Recommended firewall blocks

Analysis time: 3 minutes vs. 45 minutes manual

AI-Enhanced Threat Hunting

Traditional OWASP detection relies on predefined rules. AI enables proactive threat hunting:

Hunting Query	Detection Capability
"Find unusual parameter patterns in POST requests"	Zero-day injection detection
"Identify API endpoints with excessive error rates"	Broken access control discovery
"Show authentication patterns that deviate from baseline"	Credential stuffing detection
"Detect data exfiltration patterns in response sizes"	Data breach identification

Automated OWASP Reporting

AI generates compliance-ready OWASP security reports:

Attack attempt summary by category
Successful vs. blocked attack ratio
Top attacking IPs and geolocation
Remediation status tracking
Trend analysis over time

Example Report Query: "Generate a weekly OWASP Top 10 security report including attack trends, top threats, and remediation recommendations."

OWASP Detection ROI

Organizations implementing AI-powered OWASP detection report measurable improvements:

Metric	Before AI	After AI	Impact
Attack detection rate	72%	94%	31% improvement
False positive rate	38%	11%	71% reduction
Mean time to detect	4.1 hours	8 minutes	97% faster
Analyst time per incident	35 minutes	5 minutes	86% reduction

AI-Powered OWASP Analysis Prompt

The following prompt generates a full OWASP security report with LogZilla AI Copilot:

text
Analyze all web application security events from the past 7 days compared to
the previous 7-day period. Correlate injection attempts, authentication
failures, access control violations, and suspicious request patterns across
all web servers and WAFs. Map detected attacks to OWASP Top 10 categories
(A01-A10) and MITRE ATT&CK techniques. Include a priority matrix ranking
vulnerabilities by exploitation frequency and business impact. Identify attack
sources, targeted endpoints, and successful vs. blocked attempts. Provide
specific WAF rules, firewall blocks, and application hardening recommendations.

This single prompt generates:

OWASP Top 10 mapping with severity ratings
MITRE ATT&CK correlation for threat intelligence
Priority matrix by exploitation frequency and business impact
ModSecurity WAF rules to block detected patterns
Firewall commands for Cisco, Palo Alto, and iptables
Compliance impact assessment for PCI DSS, GDPR, and HIPAA

The AI OWASP Detection video demo shows this prompt generating a full report in just a couple of minutes, saving hours of manual analysis.

Next Steps

Implementing OWASP Top 10 detection with LogZilla requires a systematic approach. Start by deploying the parsing rules for the most critical vulnerabilities, typically injection attacks and authentication failures. Configure dashboard widgets to monitor security events in real-time, then establish automated triggers for immediate incident response. Enable AI Copilot for natural language threat hunting and automated security reporting. Organizations seeking to improve their security posture should evaluate LogZilla's AI capabilities for their specific environment and compliance requirements.

Detecting OWASP Top 10 Vulnerabilities: Complete LogZilla Guide

Introduction to the OWASP Top 10

The OWASP Top 10 2021 Complete List

Why Log Management is Critical for OWASP Top 10 Defense

LogZilla's Approach to OWASP Top 10 Detection

Micro-FAQ

What is the OWASP Top 10?

Which logs help detect OWASP Top 10 issues?

Should logs be JSON?

Which transport should be used for app logs?

Summary

A01:2021 – Broken Access Control

A02:2021 – Cryptographic Failures

A03:2021 – Injection

A04:2021 – Insecure Design

A05:2021 – Security Misconfiguration

A06:2021 – Vulnerable and Outdated Components

A07:2021 – Identification and Authentication Failures

A08:2021 – Software and Data Integrity Failures

A09:2021 – Security Logging and Monitoring Failures

A10:2021 – Server-Side Request Forgery (SSRF)

Using the LogZilla UI for Security Analysis

Dashboard Widgets for Security Monitoring

Simple UI Searches

Automated Security Response with Triggers

Brute Force Detection

Critical Injection Alert

Path Traversal Response

Advanced Correlation for Complex Attacks

When to Use API vs UI

AI-Powered OWASP Detection

AI Query Examples for OWASP Detection

Real-World AI Analysis Example

AI-Enhanced Threat Hunting

Automated OWASP Reporting

OWASP Detection ROI

AI-Powered OWASP Analysis Prompt

Next Steps

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