Understanding SAST: Code-Level Security

Static Application Security Testing (SAST) analyzes source code to find security vulnerabilities without executing the application. Think of it as a spell-checker for security—it reads your code and flags potential problems.

How SAST Works

┌─────────────┐     ┌──────────────┐     ┌─────────────┐
│ Source Code │ ──▶ │ SAST Engine  │ ──▶ │   Report    │
│ (.py, .js)  │     │ (Parser +    │     │ (Vulns +    │
│             │     │  Rules)      │     │  Locations) │
└─────────────┘     └──────────────┘     └─────────────┘

SAST tools:

1. Parse your code into an abstract syntax tree (AST)
2. Apply rules to detect vulnerable patterns
3. Report findings with file locations and remediation advice

What SAST Finds

Vulnerability Type	Example	SAST Detection
SQL Injection	query = "SELECT * FROM users WHERE id=" + user_input	Pattern matching on string concatenation in queries
XSS	innerHTML = userInput	Tracking untrusted data to DOM sinks
Hardcoded Secrets	api_key = "sk-1234abcd"	Regex patterns for API key formats
Path Traversal	open(user_path)	Tracking user input to file operations
Insecure Deserialization	pickle.loads(data)	Known dangerous function calls

SAST vs DAST: Complementary Approaches

Aspect	SAST	DAST
When	Before runtime (build phase)	During runtime (test phase)
What it sees	Source code	Running application
Coverage	All code paths	Only exercised paths
False positives	Higher (no runtime context)	Lower (validates exploitation)
Speed	Fast (minutes)	Slower (hours)
Languages	Language-specific	Language-agnostic

Types of SAST Analysis

1. Pattern Matching

Simple regex-based detection:

# Detected by pattern: password\s*=\s*["'][^"']+["']
password = "hardcoded123"  # SAST flags this

2. Data Flow Analysis

Tracks data from sources to sinks:

# Source: user input
user_input = request.args.get('query')

# ... code ...

# Sink: database query (SAST tracks the flow)
cursor.execute(f"SELECT * FROM users WHERE name = '{user_input}'")

3. Control Flow Analysis

Understands execution paths:

def process(data):
    if validate(data):  # Safe path
        safe_process(data)
    else:
        # SAST knows this path exists
        unsafe_process(data)  # May flag this

SAST Limitations

Be aware of what SAST cannot do:

• Runtime behavior: Can't detect issues that only appear at runtime
• Business logic flaws: Doesn't understand your application's intent
• Configuration issues: Usually focuses on code, not config files
• Third-party closed-source code: Can only analyze source you provide

Choosing SAST Results to Act On

Not all findings are equal. Prioritize by:

1. Severity: Critical > High > Medium > Low
2. Confidence: High confidence findings are more likely true positives
3. Exploitability: Can this vulnerability be reached by an attacker?
4. Data sensitivity: Does this affect PII, credentials, or financial data?

Next, we'll explore the top SAST tools and when to use each. :::