To keep sensitive content out of OpenTelemetry GenAI traces, first disable prompt and completion capture unless it is genuinely needed, then apply a deliberate Collector policy before export and verify the data at each pipeline boundary. Collector rules reduce exposure but cannot guarantee that every secret or piece of personal information will be detected, so prevention and testing matter as much as redaction.
Which parts of a GenAI trace can contain sensitive data?
Prompts and completions are only the most visible risks. OpenTelemetry’s GenAI span conventions warn that message content may contain user data or personally identifiable information (PII), and that system instructions may also be sensitive.
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gen_ai.input.messagesandgen_ai.output.messages: user messages, prompts, model responses, and completions.gen_ai.system_instructions: system or developer instructions.- Prompt-variable values and other runtime context.
- Tool names and descriptions, plus
gen_ai.tool.call.argumentsandgen_ai.tool.call.result. - Retrieval queries, retrieved documents, and memory content.
- Custom span attributes, events, exception messages, URLs, baggage, and logs associated with the trace.
Treat content-bearing fields as data, not harmless metadata. Sensitivity depends on the application and its payloads; OpenTelemetry does not determine which values are sensitive for you.
Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsPrevent prompt and completion capture at instrumentation time
Prevention is the strongest first control. OpenTelemetry’s GenAI conventions state: “OpenTelemetry instrumentations SHOULD NOT capture them by default, but SHOULD provide an option for users to opt in.” In context, “them” refers to model instructions, user messages, and model outputs, which the conventions describe as sensitive and often large. Check the behavior and configuration options of the specific instrumentation and version you deploy; do not assume every library has the same defaults.
#1 Best Overall
- Compatible Model(s): Magicmoon brand filter only for 24 inch -diagonally measured - widescreen monitor - aspect ratio 16:9 - filter size: width: 20 15/16", Height: 11 13/16" (531mm x 298mm)
- Superior Privacy: The computer privacy filter makes the screen appear dark when looking at it from an angle (the angle is about 30 to 60 degree), but bright when looking directly at it. To change the privacy level - simply adjust your monitor’s brightness accordingly
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- Perfect For Open Workspaces: Great for maintaining screen privacy in open work spaces
- Includes Two Options: Option 1 uses clear adhesive strips that securely attach to any computer screen. Option 2 (for computer screens with a raised bezel only) uses slide mount tabs that easily stick to the display frame, allowing you to slide the privacy screen filter on and off as needed
If a debugging workflow truly needs message content, make capture an explicit, limited choice rather than a general default. The conventions describe storing content outside the trace and recording references in spans as a way to separate access controls. That adds a storage and authorization path to manage, but can keep the main telemetry pipeline from carrying the content itself.
Truncation can reduce volume, but it is not a reliable privacy boundary: a secret or personal detail can appear at the beginning of a prompt or response. For structured payloads, preserve useful structure while removing or replacing sensitive values where feasible.
Rank #2
- Privacy Screen Filter Size: If the visible area of your display has the following dimension: Width x Height (Exclude Frame/Arrow 1 to 3 mm errors): 20 15/16" x 11 13/16" (532 mm x 299 mm), then this filter is good for you. Very Important to double check your screen's Width and Height excluding frame before ordering. It's not recommended to make your selection based solely on your screen's diagonal size
- Left and Right Privacy: Not block visibility directly behind you, regardless of distance. The privacy filter makes the screen appear dark when looking at it from an angle (left and right 30 to 180 degree), but clear when looking directly at it. To change the privacy levels, simply adjust your monitor's brightness level accordingly
- Matte and Glossy Sides: It's a reversible privacy screen filter, giving you the flexibility to choose glossy or matte finish. The matte side will have less glare, however the glossy side will have stronger privacy
- Perfect for Open Workspaces: Ensure your working space is bright and well lit. Privacy screens do not work in dimly lit areas
- Two Installation Option: Option 1 uses clear double side adhesive strips that securely attach to any computer screen. Option 2 (for computer screens with a raised bezel only) uses slide mount tabs that easily stick to the display frame, allowing you to take out the privacy screen filter easily as needed
Choose the right Collector control
The OpenTelemetry guidance on handling sensitive data describes several processors. Select according to whether the policy should change an attribute, discard a whole record, or retain only a known-safe set.
| Control | Use it for | Main trade-off |
|---|---|---|
| Disable content capture at instrumentation | Prevent prompt and completion exposure at the source. | Less direct payload visibility when debugging. (OpenTelemetry GenAI conventions) |
| Store content externally; put references in spans | Workflows that need separate content access controls. | Requires a separate storage and authorization path. (OpenTelemetry GenAI conventions) |
| Attribute processor | Deleting, changing, or hashing named attributes. | Requires knowing the attribute keys actually emitted. (OpenTelemetry sensitive-data guidance) |
| Filter processor | Dropping an entire span or record when it should not be retained. | All details in the dropped record are lost. (OpenTelemetry sensitive-data guidance) |
| Redaction processor | Keeping selected attribute keys and masking values or keys by pattern. | Bad rules can remove useful fields or allow sensitive values through. (Collector Contrib redaction documentation) |
| Transform processor | Targeted attribute rewrites and other transformations. | Rules still need to cover the payload shapes actually emitted. (OpenTelemetry sensitive-data guidance) |
The Collector Contrib redaction processor documentation describes a particularly conservative option: configure allowed_keys to retain only attributes you have chosen. An empty allowed_keys list removes all attributes; allow_all_keys: true disables that allowlist. Treat the allowlist as fail-closed only when it is intentionally configured, and check that sensitive values cannot reappear in nested structures or alternate attributes.
Rank #3
- Warning: Not compatible with iPhone 15.15 Pro, iPhone 15 Plus
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- The privacy screen protector can protect the data on the screen. Reduces viewing angle to avoid prying eyes, keeping confidential information away from third party sight.
- Provides an additional layer of privacy protection: Advanced privacy filter blocks viewing from any angle above 28° to keep what's on your iPhone 15 Pro Max (6.7 inch) screen just for your eyes.
- Ideal anti-break solution: extremely high hardness, protects the screen of your phone from accidental bumps and damage. Dust-free, fingerprint-free, push button installation, too easy, bubble-free.
Pattern rules need careful review. The processor applies blocked patterns in configured order. Allowed-value patterns take precedence over blocked-value patterns, so a broad exception can let a value through. Ignored keys bypass redaction checks; use them only for fields whose values are known to be safe.
Build and validate the sanitization pipeline
1. Inventory what your application emits
List the instrumentation libraries, SDKs, application hooks, and Collector pipelines in use. Inspect span attributes, events, resource attributes, exception data, and associated logs—not just the standard GenAI fields. Libraries and application code can add custom telemetry, so review the data that is actually emitted.
Rank #4
- 【Perfect for 16 Inch Laptop】Privacy screen for laptop modeled with a real machine to ensure a perfect match in size. Adapted to 16 inch laptop screen with 16:10 aspect ratio, width 13.60 inches (345 mm), height 8.46 inches (215 mm), Diagonal: 16" (408 mm) ,compatible with HP, Dell, Lenovo, Acer, Asus, LG, Envy, Toshiba, Samsung and other Laptop brands. You can use it anywhere you need to protect the privacy of your screen, offices,
- 【Two Attachment Options】- Installs in minutes. Option 1 uses clear adhesive strips that securely attach to any screen. Option 2 uses slide mount tabs that easily stick to the display frame, allowing you to slide the filter on and off the screen as needed.
- 【Eye Protection】 The matte finish laptop screen privacy screen prevents glare and softens harsh light. By blocking 95% of reflected light, filtering 65% of blue light and 96% of UV rays, the privacy screen filter helps to protect your privacy, minimize eye fatigue, and extend the life of your screen.
- 【Usage Scenario】 Computer anti-spy film is suitable for a variety of different scenarios. In public places, such as cafes, airports, libraries, etc., when using a computer, using anti-snooping film can prevent others from snooping on your private information. In the office, anti-snooping film can protect confidential information from the prying eyes of colleagues or competitors.
- 【Installation and Content】This computer anti-peep film is easy to install, just place it gently on the screen, adjust the position appropriately according to the size, and then fix it on the screen. At the same time, this anti-peep film is made of high-quality material, scratch and fingerprint resistant, and has a long service life. Comes with 2 PC monitor privacy screen filters, 2 sets of clear tape, 2 sets of sliding mounting tabs, and 2 microfiber cleaning cloths.
2. Decide what is permitted to leave the process
Disable unnecessary content capture first. For each field you keep, record why it is useful and whether it can contain personal data, credentials, or confidential material. Where content is needed only for a limited workflow, consider explicit opt-in or an externally stored reference rather than sending the content to every telemetry destination.
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3. Apply the policy before export
Configure the relevant processors in the active Collector pipeline. Use attribute rules for known keys, filters to discard whole records, redaction for allowlists or pattern-based masking, and transforms for targeted rewrites. Defining a processor is not enough: confirm that the intended pipeline includes it and that processing occurs before export to systems with broader access or longer retention.
Best Value
- 25° Anti-Spy Privacy Screen : Our industry-leading 25° narrow-bezel privacy technology ensures your screen is only visible to you directly in front. Anyone looking from the side will see a dark, blank screen, effectively preventing others from snooping on your sensitive personal information, messages, and financial transactions.
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4. Match rules to the actual data representation
GenAI input and output content have defined JSON schemas, but the representation can vary: a library may emit structured attributes or serialize content as a JSON string. A rule aimed at nested fields may not match a serialized value; a regular expression aimed at a string may miss other encodings or payload shapes. Check the language, instrumentation version, and resulting spans before relying on a rule.
For example, OpenTelemetry’s sensitive-data guidance shows hashing user.email and deleting user.full_name with an attribute processor. Its transform example derives a SHA-256 field from a user ID and deletes the original. These illustrate processor capabilities, not a universal anonymization guarantee.
5. Test what actually leaves each boundary
- Use controlled test traces containing representative prompt, completion, tool, retrieval, exception, and URL values.
- Inspect span attributes and events, and relevant log records, after instrumentation and again after Collector processing.
- Check whether each test value is absent, removed, or masked as intended, including alternate and serialized representations.
- Review whether replacements affect debugging, correlation, or cardinality.
- Where useful, enable redaction audit summaries for counts and keys removed or masked; keep sensitive values out of the audit channel.
- Repeat the review when libraries, semantic conventions, Collector releases, or application payloads change.
Check the rest of the trace, not only GenAI spans
Other spans can carry secrets or personal data in the same trace. OpenTelemetry’s HTTP span conventions recommend scrubbing sensitive URL query values when instrumentation can identify them; examples include sig and cloud-provider signature or credential parameters. The database client span conventions say query text should be collected by default only when sanitization excludes sensitive information, and describe replacing literals with placeholders. Review these fields alongside GenAI attributes in your policy and tests.
Hashing and pattern rules are not universal privacy guarantees
Hashing can support correlation, but predictable or low-entropy identifiers may still be guessed or reversed in practice. OpenTelemetry’s sensitive-data guidance warns about this risk; the Collector redaction documentation recommends HMAC rather than a simple hash when hashing low-entropy data is needed. Protect key material and assess whether retaining a stable identifier is appropriate for your threat model.
Likewise, regular expressions and attribute rules can only cover cases they are written to match. The official guidance does not establish a universal detector that guarantees removal of arbitrary PII or secrets from model content. Define the policy for your application, test representative payloads, and review the exported representation. Technical controls also do not by themselves determine legal or regulatory compliance; that depends on your data, deployment, jurisdiction, and organizational requirements.
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