View findings in Semgrep Cloud Platform

• Semgrep Cloud Platform
• Team & Enterprise Tier

Semgrep Code generates a finding when a rule matches a piece of code in your codebase. You can use Semgrep Cloud Platform's Findings page page to view all of the findings generated by Semgrep Code after it scans your codebase.

Navigate to the Findings page

To access the Findings page:

1. Log in to Semgrep Cloud Platform.
2. Click Code to navigate to the Findings page.

Findings page structure

The Findings page consists of:

• The filter panel, which you can use to group and filter for specific findings
• Information about findings identified by Semgrep Code. Each finding in the list includes:
  • The name and description of the rule used to generate the finding
  • The name of the project, as well as links to the Git branch and source code, where Semgrep Code identified the finding

Group findings

By default, Semgrep groups all of the findings by the rule Semgrep used to match the code. This view is called the Group by rule view. The rules that reported the highest number of findings are at the top of the page. This helps you see which rules have the highest efficiency and which generate a lot of noise in your results.

To view findings individually, toggle Group by Rule to No grouping using the drop-down menu in the header. Findings are displayed based on the date they were found, with the most recent finding listed at the top.

Filter findings

Use filters to narrow down your results. The following criteria are available for filtering:

Filter	Description
Projects	Filter by repositories connected to Semgrep Cloud Platform.
Status	Filter the triage state of a finding. Refer to the following table to understand triage states.
Category	Filter by the type of security issue or vulnerability the rule detects, such as security, correctness, and maintainability. You can select more than one category at a time. See Finding categories for information on how Semgrep categorizes your findings.
Severity	Filter by the severity of a finding. Severity is computed based on the values assigned for Likelihood and Impact by the rule's author. Possible values: Low Medium High
Component	Filter by Semgrep Assistant component tags. Semgrep Assistant uses GPT-4 to categorize a finding based on its function, such as payments, user authentication, and infrastructure.
Confidence	Filter by the likelihood of the rule to detect true positives. The higher the confidence, the more true positives the rule may detect.
Recommendation	Filter by recommendation offered by Semgrep Assistant's auto-triage feature. Possible values: Fix Ignore
Action	Filter by monitoring, commenting, or blocking rules in your Policies.
Rule	Filter by rules included in your Policies page. You can select more than one rule or ruleset for filtering.
Ruleset	Filter by the ruleset name where rules that match the code belong. More than one rule or ruleset can be selected for filtering.
Branch	Filter by findings in different Git branches.

Finding categories

A finding can be categorized in two ways:

1. Finding categorization based on the issue or code it detects:

   • Anti-patterns
   • Security vulnerabilities (such as dangerous function usage)
   • Business or logic bugs
   • Matches based on your own custom rules (such as organization-specific authentication logic)

   Semgrep rules provide a metadata schema to identify these common categories. Semgrep findings include a message field that describes the security issue or bug found in matching code. Additionally, findings can provide a fix field that fixes the issue by creating a suggestion within your source code management (SCM) tool, such as GitHub, GitLab, and Bitbucket.

2. Finding categorization based on the validity of the match:

   True positive

   Rules are written to match a certain code pattern. A true positive is a genuine match. The rule is capturing the code as intended.

   False positive

   A false positive is a mismatch between the intended purpose of the rule and the code it matched. A finding is generated but does not meet the rule's intended need. Rules with a high false positivity rate are said to be noisy.

   False negative

   A false negative is a finding that should have been found by a rule, but was not. This can happen for two reasons:

   • A flaw in the rule's logic. See Reporting false negatives.
   • A bug within Semgrep itself. See the list of Semgrep issues to file a bug report.

tip

You can identify findings categorized under Security by their badge.

Display findings reported in a specific timeframe

By default, the Findings page displays your results from all time. To display findings reported during a specific timeframe, click the All time button and select the preferred period. The following options are available:

• All time
• Last 1 year
• Last 1 month
• Last 7 days
• Last 1 day

View findings details about a specific finding

To view in-depth information about a specific finding:

1. Select the finding whose details you want to view details:
   • If the default Group by Rule is enabled, click the Details icon on the card of the finding.
   • If the No grouping view is enabled, click the header hyperlink on the card of the finding. In the example on the screenshot below, it is the detected-generic-api-key.

Add notes to findings

To add notes to the activity history of a finding:

1. Select a finding where you want to view details or add notes, and then do one of the following actions:
   • If the default Group by Rule is enabled, click Details icon on the card of the finding.
   • If No grouping view is enabled, click the header hyperlink on the card of the finding. In the example on the screenshot below, it is the detected-generic-api-key.
2. View, or add the notes in the Activity section. To add a new note, click plus New note.

Dataflow traces

With dataflow traces, Semgrep Code can provide you with a visualization of the path of tainted, or untrusted, data in specific findings. This path can help you track the sources and sinks of the tainted data as they propagate through the body of a function or a method. For general information about taint analysis, see Taint tracking.

When running Semgrep Code from the command line, you can pass in the flag --dataflow-traces to use this feature.

You can view dataflow traces in:

• Semgrep Cloud Platform by going to Semgrep Code's Findings page. For more details, see Path of tainted data in Semgrep Code.
• The PR or MR comments created by Semgrep Code running in your CI/CD system. To enable this feature, see:
  • GitHub users: Dataflow traces in PR comments
  • GitLab users: Dataflow traces in MR comments

Get cross-file findings

To get cross-file (interfile) findings in your organization, follow the steps in Enabling Semgrep Pro Engine. See Semgrep Pro Engine overview for general information about Semgrep Pro Engine.

View dataflow traces

Prerequisite

Not all Semgrep rules or rulesets make use of dataflow traces, or taint tracking. Ensure that you have a ruleset, such as the default ruleset added in your Policies page. If this ruleset is not added, go to https://semgrep.dev/p/default, and then click Add to Policy. You can add rules that use taint tracking from Semgrep Registry.

To view the detailed path of tainted data with dataflow traces:

1. Log in to Semgrep Cloud Platform, and click Code in the left panel to view your findings.
2. Select the finding you're interested in, then do one of the following actions:
   • If the default Group by Rule is enabled, click View details icon on the card of the finding.
   • If No grouping view is enabled, click the header hyperlink on the card of the finding. In the example on the screenshot below, it is the tainted-sql-string.
3. In the Data flow section, you can see the source, traces, and sink of the tainted data. The example below displays the path of tainted data across multiple files because Semgrep Pro Engine was enabled.

Data retention

The retention period for findings is 5 years.

Further reading

• Learn how to triage and remediate Semgrep Code findings.
• See Semgrep Assistant for Semgrep Code for information on receiving GPT-4-powered security recommendations when reviewing your findings.

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