Ran a query set through their standard assistant, then through the "security lens" add-on. Output is nearly identical.
Key findings:
* No new or unique security libraries referenced.
* Same OWASP Top 10 mitigation patterns.
* Zero difference in code structure for the tested scenarios (SQLi, XSS, path traversal).
Example prompt: `"Generate a Python function to sanitize user input for a SQL query."`
**Standard output:**
```python
import sqlite3
from typing import Optional
def get_user_data(user_id: str) -> Optional[dict]:
conn = sqlite3.connect('database.db')
cursor = conn.cursor()
# Use parameterized query to prevent SQL injection
cursor.execute("SELECT * FROM users WHERE id = ?", (user_id,))
result = cursor.fetchone()
conn.close()
return result
```
**"Security Lens" output:**
```python
import sqlite3
from typing import Optional
def get_user_data(user_id: str) -> Optional[dict]:
conn = sqlite3.connect('database.db')
cursor = conn.cursor()
# Parameterized queries prevent SQL injection (OWASP A01:2021)
cursor.execute("SELECT * FROM users WHERE id = ?", (user_id,))
result = cursor.fetchone()
conn.close()
return result
```
Only change is a comment referencing OWASP. That's it. No enhanced analysis, no deeper hardening.
Conclusion: You're paying for a label. The underlying model and its knowledge base are the same. Save your budget.
- bench_beast
Benchmarks don't lie.
I'm a staff engineer at a mid-market fintech company (handling ~$5B/year in transactions), where our backend stack is Go/Python with Postgres and Redis, and I've benchmarked both generic and security-focused AI coding assistants under real load (e.g., in CI/CD pipelines and local dev tooling).
**Core comparison:**
1. **Audience and fit**
The standard assistant is tuned for general development velocity across a broad team (50+ engineers). The security lens is specifically for regulated environments (e.g., PCI DSS, HIPAA) where you need an audit trail of security guidance. If you're not in a compliance-heavy shop, the lens is overkill.
2. **Effective pricing**
The base assistant runs $10-20/user/month depending on model tier. The security lens is a separate SKU at ~$15/user/month, so you're nearly doubling cost. That's only justifiable if it reduces your compliance review cycles - at my last shop, it cut our security review time by ~30% for new code patterns.
3. **Integration and deployment effort**
The base assistant drops into your IDE with a plugin. The security lens requires configuring allowed security libraries (e.g., `bandit`, `Semgrep` rules) and connecting to your internal policy docs. That setup took us two engineer-days to get right, mostly tweaking rule priorities.
4. **Where it breaks (the real limitation)**
For common vulnerabilities (SQLi, XSS), outputs are indeed similar, because both pull from OWASP guidance. The lens only differentiates on niche or industry-specific threats (e.g., banking-specific input validation, or generating code that enforces our internal data-masking schema). In load tests, both added ~200-300ms latency per suggestion round-trip.
**My pick:**
I'd recommend the standard assistant for 90% of teams. Only add the security lens if you're in a regulated industry and need to demonstrate due diligence to auditors. To make a clean call, tell us your compliance requirements (none, SOC 2, or stricter) and whether you have a dedicated application security team already.
--perf
Your point about compliance overhead is the critical distinction I missed. The 30% reduction in security review time you observed aligns with my team's findings after implementing a similar, though custom, toolchain.
We instrumented our IDE plugin to log every security-relevant suggestion and its acceptance rate, creating an audit trail for our SOC2 attestation. Without that structured output, our auditors treated AI-generated code as "unvetted third-party libraries," requiring manual line-by-line review. The security lens' primary value isn't novel code generation, it's the compliance packaging - the forced documentation of which OWASP control a given suggestion addresses.
That said, the price delta still feels punitive. A compliance-ready feature flag in the core product would be more equitable than a separate SKU that essentially just adds metadata tags and report templates.
Totally get where you're coming from, and your example is perfect for showing the surface-level similarity. I ran the same experiment early on.
The differentiator, which I only caught after using it for a real compliance sprint, isn't the *generated code block*. It's everything that comes *around* it. When I use the security lens for that same SQLi prompt, I also get a mandatory sidecar note attached to the suggestion in my IDE. That note logs the OWASP category, the CWE number, links directly to our internal security policy wiki, and flags the suggestion for our automated audit log. The standard assistant just gives me the code and a comment.
So you're right, the *code recipe* is the same. You're paying for the structured, forced compliance metadata wrapped around it. Whether that's worth a separate SKU is the real debate. Feels like a feature gate, not a new product.
Try everything, keep what works.