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[content]
DeepSource: The AI Code Review Platform
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Platform
Deep code review with hybrid static analysis and AI agents.
High-signal, low false-positive issues and structured feedback across security, quality, complexity, and coverage.
Inline review on pull requests
Catch bugs, anti-patterns, and security vulnerabilities on every pull request. Powered by 5,000+ deterministic rules along with our state-of-the-art AI review agent.
deepsource
bot
reviewed
a few minutes ago
deepsource
bot
left a comment
DeepSource reviewed changes in the commit range
b76c8fa...63debb2
on this pull request. Below is the summary for the review, and you can see the individual issues we found as review comments.
payments/reconciliation.py
Comment on lines
+142
to
+144
142
+
for merchant_id, txn_group in groupby(
143
+
pending_transactions, key=lambda txn: txn.merchant_id
144
+
):
deepsource
bot
a few minutes ago
itertools.groupby
without sorting causes incorrect grouping
The code uses
itertools.groupby
on
pending_transactions
, a queryset without a guaranteed order.
groupby
only groups consecutive elements with the same key. If transactions for the same merchant are not adjacent, they will be settled in separate batches, leading to duplicate payouts.
Add a sort operation on
pending_transactions
by
merchant_id
before the
groupby
call. This ensures all transactions for the same merchant are grouped together for a single settlement.
invoicing/services/export.py
Comment on lines
+78
to
+81
78
+
result = subprocess.run(
79
+
cmd,
80
+
shell=True,
81
+
capture_output=True
deepsource
bot
a few minutes ago
Potential command injection vulnerability with
shell=True
Using
subprocess.run
with
shell=True
to generate invoice PDFs can lead to command injection if the
cmd
variable includes merchant-supplied data such as invoice numbers or company names. This is a security risk that could allow attackers to execute arbitrary commands on the server.
Consider using
shell=False
and passing the command as a list of arguments instead. This prevents shell interpretation of special characters in merchant-provided input.
api/middleware/auth.py
Comment on lines
+53
to
+55
53
+
api_key = request.headers.get("X-Api-Key")
54
+
if api_key:
55
+
merchant = db.query(Merchant).filter(Merchant.api_key == api_key).first()
deepsource
bot
a few minutes ago
API key comparison vulnerable to timing attacks
The merchant API key is compared directly using
==
which is vulnerable to timing attacks. An attacker could potentially recover the key character by character by measuring response time differences, compromising merchant accounts and payment data.
Use a constant-time comparison function like
secrets.compare_digest()
to prevent timing-based side-channel attacks on sensitive API key comparisons.
Autofix™
Verified, pre-generated patches for most issues, so you can fix issues faster without breaking your flow.
String-based query with
JSON_EXTRACT
risks SQL injection
The code constructs an SQL DELETE statement by directly formatting self.table_name into the query string and using user-controllable parameters with JSON_EXTRACT.
Critical
Security
AI REVIEW
472
with self._get_cursor() as cur:
473
try:
474
# Use JSON_EXTRACT for JSON field access
475
cur.execute(
476
f"DELETE FROM `{self.table_name}` WHERE JSON_EXTRACT(meta, %s) = %s", 1
477
(f"$.{key}", value),
478
)
479
except Exception as e:
480
logger.warning("Error deleting by metadata field: %s", e)
481
raise
api/core/rag/datasource/vdb/doris/doris_vector.py
Autofix™
Pull request gates
Define guardrails and prevent pull requests from merging when the PR quality is not satisfactory.
Some checks haven't completed yet
5 pending checks
5 pending checks
DeepSource: Python
Waiting for status to be reported — Analysis in progress...
DeepSource: JavaScript
Waiting for status to be reported — Analysis in progress...
DeepSource: Test coverage
Waiting for status to be reported — Analysis in progress...
DeepSource: Secrets
Waiting for status to be reported — Analysis in progress...
DeepSource: package.json
Waiting for status to be reported — SCA in progress...
PR Report Card
More than just issues. Structured feedback to your AI agent to help improve quality of any pull request.
PR Report Card
Security
4
Reliability
19
Complexity
3
Hygiene
0
Coverage
11
Overall PR Quality
Focus Area
Reliability
Guidance
Fix the high-severity
_check_milestones
call outside transaction risk in contrib/referrals/team_referral.py to prevent inconsistent states.
Secrets Detection
Prevent API keys, tokens, and sensitive credentials from ever reaching production. Validated against 165+ providers.
OSS Vulnerability Scanning
See which dependency vulnerabilities actually affect your code with reachability and taint analysis.
Code Coverage
Track coverage and see which lines in your code are untested. Enforce thresholds so nothing ships without tests.
Compliance Reporting
Stay audit-ready with security vulnerability reports mapped to OWASP® Top 10 and SANS Top 25.
Infrastructure-as-Code Review
Catch security misconfigurations in Terraform and CloudFormation before they become incidents.
License Compliance
Catch copyleft and restrictive OSS licenses before they create legal risk for your product.
MCP Server
Feed review insights and structured feedback directly into your AI coding agent or any MCP-compatible app.
API & Webhooks
Bring DeepSource into your workflows with a full GraphQL API and real-time webhook events.
Full Codebase Review
Go beyond pull requests. Scan your entire existing codebase and track code health and security hotspots over time.
With DeepSource's pull request analysis workflow, everything is integrated — right at the point of merge, and this has been a game changer for us.
Reed Wilson
,
Engineering Manager
Benchmarks
Highest F1 score on the OpenSSF CVE Benchmark.
The only code review engine that's simultaneously precise and thorough.
F1 Score on OpenSSF CVE Benchmark
DeepSource
84.51%
Cursor BugBot
80.45%
Devin Review
78.08%
OpenAI Codex
77.70%
Greptile
68.61%
Claude Code
62.40%
Semgrep (CE)
36.70%
CodeRabbit
36.00%
What's F1 Score?
The harmonic mean of precision and recall. F1 is the only metric that punishes both failure modes: missing real vulnerabilities and crying wolf on safe code. It can't be gamed by being too conservative or too noisy.
About this benchmark
The OpenSSF CVE Benchmark consists of code and metadata for over 200 real-life security vulnerabilities in JavaScript and TypeScript, which have been validated and fixed in open-source projects.
It evaluates tools on two key metrics: their ability to detect the vulnerability (avoiding false negatives) and their ability to recognize the validated patch (avoiding false positive).
Enterprise Ready
Code review intelligence for startups and Fortune 500s.
DeepSource is secure by design and built for scale.
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Connected repositories
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Teams on platform
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Uptime
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The AI Code Review Platform for fast-moving teams and their agents.
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