Certified: The GIAC GCLD Audio Course

Logs are evidence, and that simple fact explains why attackers so often try to alter them, delete them, or make them unreliable. In this episode, we focus on protecting log integrity, because a logging program is only as useful as the trust you can place in its records during an investigation. If an attacker can tamper with logs, defenders may lose the ability to establish timelines, attribute actions to identities, or prove what data was accessed, which turns response into a debate rather than an evidence-driven process. Even without an attacker, weak integrity controls allow accidental deletions, retention misconfigurations, and access sprawl that quietly degrade your ability to investigate incidents months later. Integrity is not just a technical property, it is also an operational discipline, because the people who run production systems are often not the same people who should have power over evidence. Protecting log integrity means designing for adversarial pressure and human error at the same time. When logs are treated like evidence from the start, you build an environment where investigations and audits rely on records you can defend.

Before we continue, a quick note: this audio course is a companion to our course companion books. The first book is about the exam and provides detailed information on how to pass it best. The second book is a Kindle-only eBook that contains 1,000 flashcards that can be used on your mobile device or Kindle. Check them both out at Cyber Author dot me, in the Bare Metal Study Guides Series.

Centralizing logs to a protected account or dedicated security boundary is the foundational design choice that makes integrity controls practical at scale. When logs remain scattered across the same accounts and projects where workloads run, the identities that can operate production systems can often also alter the evidence that describes what happened in those systems. A protected boundary reduces that risk by making the log archive its own environment with its own access controls, ownership model, and change processes. Centralization also makes investigation and response faster, because analysts can search across the organization without fighting account-by-account access barriers. Most importantly for integrity, centralization reduces the number of places where logs can be deleted or modified, which reduces the attacker’s options. It also encourages standard retention and consistent protection controls, which prevents the common pattern where some accounts keep logs for months while others keep them for days. A dedicated security boundary turns log protection from a best effort practice into an architecture property. In mature programs, this boundary is treated as evidence infrastructure, not as a convenience bucket for storage.

Immutability controls are what transform centralized logging into protected evidence, because they prevent deletion or modification even when a privileged identity is compromised. Immutability can be implemented through write-once or append-only semantics, retention locks, object versioning combined with legal-hold style protections, or other mechanisms that make retroactive alteration difficult or impossible within the retention period. The key principle is that logs should be easy to write and hard to erase, because investigations depend on historical truth. Immutability must also account for policy changes, because an attacker may not delete individual objects if they can instead change retention rules to allow rapid expiration. A strong design therefore protects both the log data and the configuration that governs its lifecycle, with separate ownership and alerting for policy changes. Immutability is not just about defending against a malicious insider or external attacker, it is also about preventing well-meaning administrators from cleaning up evidence to solve a storage problem. When immutability is in place, defenders can assume the record is stable, which changes how confidently they can act during response.

Encryption should be applied in transit and at rest for log stores, not because encryption alone guarantees integrity, but because it protects confidentiality and reduces the chance that evidence is exposed or manipulated through interception. Encryption in transit ensures that logs moving from sources to the centralized archive are protected from network-based interception or alteration during delivery. Encryption at rest ensures that the stored evidence is protected from unauthorized access in the storage layer and reduces the impact if storage systems are exposed through misconfiguration or credential compromise. In many environments, encryption is enabled by default, but a security-by-default approach still verifies that encryption is consistently applied and that key management expectations match the sensitivity of the log data. Logs often contain sensitive information, including identity details, resource names, and sometimes data access patterns that can reveal business operations, so confidentiality matters. Encryption design must also consider key access, because if attackers can access encryption keys broadly, they may gain the ability to decrypt and analyze logs even if storage permissions are strong. Proper encryption practices support the overall evidence model by ensuring that evidence is both protected and handled in a way that is defensible to auditors and stakeholders. Encryption is therefore a necessary layer in a broader integrity strategy, not a substitute for immutability and access control.

Write permissions should be restricted to logging services and controlled ingestion paths, not to humans, because human write access is one of the easiest ways to introduce tampering risk. The cleanest model is that log producers can write logs through well-defined mechanisms, and no human identity has the ability to manually edit or overwrite stored logs. If humans can write to the archive, attackers who compromise human accounts can insert misleading entries, delete files by overwriting them, or corrupt formats to break parsing and search. Even when the risk is not malicious, human write access increases accidental damage, such as an operator attempting to reorganize storage paths and unintentionally altering retention or access controls. Restricting write permissions also makes change control simpler, because the ingestion pipeline becomes the only sanctioned path for new data to enter the archive. This improves integrity because you can monitor and validate that pipeline, including what sources are expected and how data should look. When ingestion is constrained and predictable, anomalies like unexpected sources or missing streams become easier to detect. A strict write model is one of the most effective integrity controls because it narrows the ways evidence can be influenced.

Read permissions must also be restricted by role and need-to-know, because logs are sensitive and because broad read access creates both privacy risk and an attacker advantage. If too many people can read centralized logs, then a compromised account can use those logs to discover infrastructure, identify targets, and learn detection patterns, which accelerates attacker progress. A least-privilege read model typically separates investigative read access from routine operational access, ensuring that only those who need organization-wide visibility can query the full archive. It also supports segmentation, where some teams can view logs for their own workloads while a smaller group can view cross-environment evidence needed for enterprise investigations. Read restrictions should be implemented with clear role definitions and access review processes, because log access tends to expand quietly over time as people request it for troubleshooting and then never relinquish it. Strong read controls also support compliance by limiting who can see sensitive identity and access data. The goal is to preserve the usefulness of centralized logs without turning them into a widely accessible treasure map. In practice, tightly controlled read access improves both security and the defensibility of how evidence is handled.

Designing a least-privilege model for a log archive requires thinking about the archive as a service with distinct responsibilities rather than as a shared folder. There are identities that produce logs, identities that manage ingestion and storage configuration, identities that search and analyze logs, and identities that audit access and policy changes. Each of those responsibilities should be separated, and permissions should be scoped to the minimum actions required, such as write-only for producers, configuration management for archive owners, read-only for analysts, and audit visibility for oversight roles. It also helps to define break-glass access paths explicitly, because incident response may require urgent access, but those paths should be tightly controlled, time-bounded, and logged. The model should also include restrictions on destructive capabilities, such as deleting logs or changing retention, and those capabilities should require additional approval and be limited to a small set of identities. When the model is designed clearly, it becomes easier to implement consistent controls and to explain them during audits and post-incident reviews. A good least-privilege design is one where every permission can be justified by a specific responsibility, and no permission exists simply because it might be convenient.

A common pitfall is allowing administrators to delete logs without oversight, which effectively destroys the concept of logs as evidence. In many organizations, administrators have broad permissions out of habit, and those permissions often include the ability to change retention, delete storage objects, or disable logging sources when troubleshooting. That model may feel operationally efficient, but it creates a single point of failure where a compromised administrator account can erase evidence and slow or derail investigations. It also creates internal risk, because a well-meaning cleanup effort can remove logs that later become critical for a long-running investigation. Oversight matters because destructive actions should be rare and should leave a trace that is reviewed independently. If an environment allows quiet deletion, it will eventually suffer either from accidental evidence loss or from deliberate tampering, and the result will be the same: uncertainty during an incident. The integrity goal is to make evidence difficult to destroy, even for privileged accounts, and to ensure that any destructive attempt is highly visible. In other words, administrators should be able to operate systems, but they should not be able to rewrite history.

A quick win that dramatically improves integrity is to separate log archive owners from production operators, because it reduces conflict of interest and reduces the impact of compromise. Production operators often need broad access to fix outages and deploy changes quickly, and those permissions can become attractive targets for attackers. If the same identities can also alter the log archive, then compromise of a production operator can become compromise of evidence. Separation creates a different security boundary where archive management is handled by a distinct group with different credentials, different approval paths, and ideally different authentication enforcement. It also improves governance, because the archive owners can act as independent stewards of evidence, able to support investigations and audits without being tied to the same incentives as production change velocity. Separation does not require a large team, but it does require deliberate role definition and access boundaries. Even small organizations can implement separation by using dedicated accounts, role-based access, and restricted administrative rights for the log archive. This quick win works because organizational structure is itself a security control, and it is often easier to change than complex technical systems.

A breach scenario where an attacker attempts log tampering is worth rehearsing because it exposes whether integrity controls are real or merely assumed. In such a scenario, the attacker gains privileged access in a production environment and then tries to reduce visibility by disabling log sources, changing log destinations, shortening retention, or deleting stored logs. If logs are centralized, immutable, and protected by tight permissions, the attacker may succeed in disrupting local logging but still fail to erase the centralized record, leaving a clear trail of their attempt. Responders can treat any attempt to alter logging as a high-severity signal, because it indicates awareness of detection and an intent to conceal activity. The response should include preserving evidence, validating the integrity of the archive, and verifying whether any policy changes occurred in the archive boundary itself. It should also include reviewing access to the archive to determine whether the attacker’s identity could have reached it, and whether any unusual access occurred. When rehearsed, this scenario teaches teams to defend the logging system as a primary target, not as an afterthought. It also reinforces that integrity is tested when an attacker is already inside, not when everything is calm.

Monitoring for integrity violations is the ongoing discipline that keeps the archive trustworthy over time. Integrity violations can include sudden retention changes, policy edits that broaden access, changes that allow deletion, unexpected configuration updates to immutability controls, or disruptions in expected log ingestion patterns. Sudden drops in log volume from a source can indicate logging was disabled or that the source is no longer sending data, both of which warrant investigation. Changes in who can access the archive, especially expansions of write or delete permissions, should be treated as high-risk events and reviewed quickly. Monitoring should also watch for unusual read patterns, such as large-scale log exports or queries that span many environments, because that can indicate either an investigation or an attacker harvesting evidence for reconnaissance. The key is to monitor both the log content and the controls that protect logs, because tampering often begins with changing the protections rather than directly touching objects. When integrity monitoring is in place, defenders are more likely to detect sabotage attempts early, before evidence is lost. Over time, this monitoring becomes part of the health model for the logging program, similar to how availability monitoring is part of the health model for production services.

A memory anchor that fits log integrity is a sealed evidence bag in locked storage. Evidence is valuable only if it is handled in a way that preserves chain of custody and prevents tampering, and that requires both physical protection and procedural discipline. Centralizing logs into a protected boundary is like putting evidence into the locked room rather than leaving it on a desk in the production area. Immutability controls are like sealing the bag so it cannot be opened and altered without leaving clear signs. Encryption is like ensuring the evidence cannot be read by unauthorized parties even if someone gets near it. Tight write permissions are like restricting who can place evidence into the bag, ensuring entries are controlled and predictable, while tight read permissions are like restricting who can handle the bag and inspect the contents. Separation of duties is like having a dedicated evidence custodian rather than letting every operator manage evidence as part of their routine work. When teams remember the sealed evidence bag, they naturally think about logs as assets that must be protected against both attackers and convenience-driven shortcuts.

As a mini-review, protecting log integrity depends on centralization to a protected account or dedicated security boundary so evidence is not controlled by the same identities that operate production systems. Immutability controls prevent deletion or modification, which preserves historical truth even under compromise. Encryption in transit and at rest protects confidentiality and reduces interception and exposure risk for log data and its movement. Tight permissions restrict write capabilities to logging services and controlled ingestion paths, not humans, and restrict read access by role and need-to-know to reduce reconnaissance risk and privacy exposure. Separation of duties, especially separating archive owners from production operators, reduces the impact of compromise and improves governance. Monitoring for integrity violations, such as sudden retention changes, policy edits, and ingestion disruptions, keeps the archive trustworthy over time. When these controls are implemented together, logs become defensible evidence rather than fragile telemetry.

To conclude, verify your log store cannot be easily deleted, because the integrity of evidence depends on making destruction difficult and highly visible. That verification should include confirming immutability settings, retention protections, and restrictive delete permissions in the archive boundary, as well as ensuring that policy changes affecting deletion or retention are monitored and alerted. It should also include confirming that no routine administrator role has the authority to disable logging or erase stored evidence without independent oversight. If you can confidently say that an attacker who compromises a production administrator cannot quietly destroy your centralized logs, you have achieved a meaningful integrity milestone. Once deletion resistance is confirmed, you can build stronger detection and investigation workflows on top of evidence you can trust. Verify your log store cannot be easily deleted.