Over the decades, enterprises have made significant investments in Network/Firewall security, Zero trust architecture, IAM Governance, Encryption, SIEM/SOC, Audit Frameworks and secured production environment to a major degree. However, a question that we need to answer is: Production troubleshooting process secure enough? Can Production artifacts leak during troubleshooting process? We are seeing 4 major security gaps in the current production troubleshooting process:
1) Untrusted Tools Running Inside Production
2) Confidential Data secretly Spills everywhere
3) Diagnostic Data with No Gatekeepers
4) Plain-Text Exposure of Sensitive Data
5) LLMs Learning from Your Production Data
Let’s discuss them in detail in this post.
Video
Watch the full webinar recording to learn practical strategies, real-world scenarios, and actionable insights on securing production troubleshooting and preventing diagnostic artifacts from becoming security risks.
1) Untrusted Tools Running Inside Production
Engineers use vendor tools, home-grown scripts, or ad-hoc commands during production incidents to capture troubleshooting artifacts. Many vendor troubleshooting tools are downloaded and executed directly on production servers without a formal security review, which creates potential supply-chain and data-exfiltration risks. Home-grown scripts often evolve over time without proper governance, auditing, or version control, and may run with elevated privileges that expose sensitive system information. Ad-hoc troubleshooting approaches are even more problematic because engineers execute different commands under pressure, leading to inconsistent artifact collection
Solution: Enterprises can use standardized yc-360 open source script. This script captures 16 different artifacts (Application Log, Thread Dump, Heap Dump, Heap Substitute, GC Log, netstat, vmstat, ping, top, top -H, metadata, ps, dmesg, kernel parameters…) that are necessary to troubleshoot production problem from the application stack in a pristine format. yc-360 open-source script captures artifacts in an non-intrusive mode, runs with minimal performance overhead & prevents unauthorized data transmission.
Fig: Artifacts captured by yc-360 Open-Source Script
2) Confidential Data secretly Spills everywhere
When a monitoring tool generates production outage alert, troubleshooting artifacts (thread dump, heap dump, application log, netstat…) are captured from the application stack for diagnosing the problem. These troubleshooting artifacts contain sensitive information such as customer PII data, SSN, Credit Card Numbers, VAT, IP Addresses, … Several organizations classify these datasets as confidential data. Is this confidential data properly handled? Let’s zoom how this data is handled today in most enterprises:
1) Monitoring tool generates alert
2) SRE Engineer signs in to the production servers and captures troubleshooting artifacts (thread dump, heap dump, application log, netstat…).
3) SRE Engineer uploads these artifacts to a shared drive.
4) Developer downloads the artifacts from the shared drive to his local laptop for analyzing these artifacts
5) External Vendor may download these artifacts from the shared drive to their environment for further analysis.
Now let’s take a step back and see where all these production artifacts are stored.
- In step #2 they are stored in Production Server
- In step #3 they are stored in Shared Drive
- In step #4 they are stored in Developer Laptop
- In step #5 they are stored in Vendor’s Environment
Once analysis is completed, most likely these artifacts are not deleted from these locations. It’s a huge security risk for the organization to have their sensitive confidential data dispersed in so many locations.
Fig: Confidential Data distributed everywhere
Solution: When you use yc-360 open-source script, it not only captures all the troubleshooting artifacts, but it can also transmit them securely to central yCrash server. yCrash sever analyzes these artifacts and generates a root cause analysis report. Engineers will have access only to the analyzed report and no one will have access to the raw artifacts. All the raw troubleshooting artifacts are safely archived in the yCrash server.
yCrash also provides incident retention feature. Using this capability, you can specify that incidents which are more than 6 months should be deleted. Based on the configuration, yCrash will automatically purge all the raw artifacts and it’s associated incident reports that are more than 6 months older. So, you don’t have to worry about archiving, managing, purging the artifacts.
3) Diagnostic Data with No Gatekeepers
Another serious challenge in the current approach, there is no clear way to track who are the Software Developers, QA Engineers, SRE Engineers (or external vendors) that have access to confidential data. In case we have to do any forensic, there is no clear audit trial.
Solution: yCrash reports are guarded by proper authentication and authorization mechanism.
- Authentication: yCrash supports Single Sign-On (SSO) through SAML integration, enabling secure and seamless authentication for users across various platforms like Okta, OneLogin, Active Directory, ForgeRock. By configuring the SSO settings, enterprises can centralize authentication, reduce the need for multiple login credentials, and enhance security through a streamlined access process. Without exposing critical information.
- Authorization: yCrash includes robust authorization controls, ensuring that only authorized personnel can access specific data and features within the platform. These controls help safeguard sensitive information and maintain compliance with organizational security policies, allowing for fine-grained access management tailored to the needs of your team.
- Audit Trial: yCrash also maintains complete audit trial of the users who access the incident reports, what paged in the incident report they navigate… So, in the case if you need to any forensic or post-mortem analysis of any security breach, it can be easily achieved through yCrash.
4) Plain-Text Exposure of Sensitive Data
When Developers are troubleshooting memory problems, they analyze Heap Dump files. Heap Dump is basically a snapshot of all the objects in memory. Thus if your applications process sensitive data such as SSN, Credit Card Number, VAT, PII data… all these data will be present in the Heap Dump. Engineer who analyzes these artifacts will be able to see them in clear text as shown in the screenshot below. This is a serious data exposure risk to the enterprise.
Fig: Heap Dump contains confidential information in clear text
Solution: yCrash provides the capability to sanitize the raw data in the Heap Dump. Whenever heap dump comes, yCrash server sanitizes the heap dump for sensitive data (e.g., char arrays, byte arrays). It replaces the actual values with asterisks (*).
The sanitized heap dump will be written to disk, ensuring that no sensitive data is stored in its original form. The yCrash server analyzes the sanitized heap dump and will generate a heap report. In the heap report, sensitive values are displayed as asterisks (*), ensuring that no confidential information is exposed. Thus even if Heap Dump lands in wrong hands they wouldn’t be able to do anything with it.
Fig: Confidential information removed by yCrash
5) LLMs Learning from Your Production Data
With everyone moving to AI, many engineers are now uploading troubleshooting data like thread dumps, heap dumps, GC logs or application logs to AI tools to speed up analysis. And these files often have sensitive information such as customer personal details, internal architecture, database queries, passwords and secret code. When this data is uploaded to outside AI services, companies may accidentally share information with third-party AI providers. In some cases, this data may also be used to improve or train AI models based on the providers rules. This creates a risk of sensitive data leaking out.
Solution: yCrash includes an integrated AI assistant called yCrash Buddy. Instead of engineers manually uploading artifacts to external AI tools, the analysis happens within the yCrash platform. Organizations can configure corporate-approved LLMs (such as Copilot, OpenAI, or other enterprise LLM deployments) to power the assistant. Before any data is sent for AI analysis, yCrash Buddy passes the artifacts through an intelligent scanning and sanitization layer that detects and removes PII and other sensitive information from the traces. Only sanitized diagnostic context is transmitted to the LLM, ensuring that production secrets and customer data are never exposed. This allows teams to benefit from AI-assisted troubleshooting while maintaining strict security and compliance controls.
Proactively Identifying PII Data
Fig: yCrash’s Proactive Analysis to Identify PII data in Troubleshooting Artifacts
yCrash Log also provides the ability to scan production artifacts, such as application logs, thread dumps, GC logs, and other diagnostic files to detect the presence of PII and sensitive data. This capability helps engineering teams identify where confidential information is accidentally gets shared in logs or traces. Developers can run this analysis in pre-production environments to proactively discover PII exposure within their application artifacts and remediate the issue by masking, removing, or redesigning the logging behavior. By detecting these leaks early, organizations can significantly reduce the risk of sensitive customer data being exposed during production troubleshooting or shared with external tools.
Conclusion
Over the years, production security has matured a lot, however incident responsive security hasn’t much. Now is the time to make use of yCrash and secure it.
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