How important is it to store your SIEM logs in a tamper-proof database?

Introduction

Imagine you’re a cybersecurity professional, and one of your clients has been attacked. You know this because all the data from their SIEM system is intact and hasn’t been tampered with – but there are also no clues as to who the attacker was or what they did next. So, how do you prove that an intrusion actually happened?

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There are three main methods (or “processes”) that SIEM systems use to store your data. None of these today are cryptographically tamperproof

There are three main methods (or “processes”) that SIEM systems use to store your data. None of these today are cryptographically tamperproof, but they do offer varying levels of protection from unauthorized changes and deletions.

Append-only database – The first and most straightforward method is the append-only database. This type of system allows you to add new events and their associated attributes but does not allow you to delete or modify any existing data once it’s been added. This process is useful for storing old logs because it keeps them available indefinitely while still protecting them against tampering by other users on the same system.

Data retention policy – Another common way SIEMs store information is through a data retention policy that dictates which historical events should be kept permanently while others may be deleted after some period of time (e.g., 60 days). In this case, your system has some level of control over what information will end up being stored long-term; however since there’s no guarantee about how long any given piece of information will remain accessible before being automatically removed from storage by its expiration date, this method isn’t considered “tamperproof” either in our opinion

Append-only databases with cryptographic verification are an alternative to traditional SIEM databases.

Immutability can be a good thing, and when it comes to storing data in an immutable database, it means that you don’t have to worry about anyone modifying the data you’ve stored. Immutable databases are also known as append-only or write-once databases.

Immutability is one of the many features provided by immudb, which is an immutable database that stores data in an append-only format and provides cryptographic verification of the data stored within it. This makes immudb an excellent alternative to traditional SIEM databases that have been shown to be vulnerable to tampering by attackers who gain access to them.

However, immudb isn’t used as a replacement for traditional SIEM data stores; rather, it’s used as an additional store for specific types of sensitive data that need extra protection from tampering but don’t fit into a traditional SIEM architecture (for example personal medical records).

When a network intrusion has happened how can you trust the data stored in traditional SIEM stores like Splunk or IBM QRadar?

If you’re storing your SIEM logs in a traditional SIEM store like Splunk or QRadar, how can you trust the data?

When a network intrusion has happened how can you trust the data stored in traditional SIEM stores like Splunk or QRadar? Traditional SIEM stores like Splunk have been compromised many times over the years and when this happens, attackers are able to modify their log entries.

If an attacker gains access to your environment they know where all of your critical assets are located within the infrastructure. They would then focus their efforts on modifying any logs that may expose them as being responsible for deleting or changing the information on these systems. At this point, it is too late because even if a forensic investigation took place afterward there wouldn’t be any way of knowing if what was modified was done by an authorized user account as opposed to someone who had gained unauthorized access via an exploit against this system itself (i.e., backdoors).

An immutable database ensures that once recorded, data is kept safe regardless of subsequent attacks or tampering.

An immutable database ensures that once recorded, data is kept safe regardless of subsequent attacks or tampering. This is critical in the context of a SIEM system because it takes organizations an average of 270 days to realize they have been hacked. So having true and untampered information about what was done by the bad actors and how they got it is of paramount urgency.

Immutable databases lend themselves to forensic analysis once an accident has been detected.

However, consumer laws in Europe and the US, like GDPR, require data to have the ability to be deleted. So, how can an immutable database comply with these regulations?

However, consumer laws in Europe and the US, like GDPR, require data to have the ability to be deleted. So, how can an immutable database comply with these regulations?

There are a few ways that allow for the deletion of data within a tamperproof database:

  • Deletion by time – this is where you set up your system so that after a certain period of time (e.g., 90 days), all records older than that period are automatically deleted from storage. This method allows you to keep only those records you need on record while still following consumer law requirements around data retention periods. It also means that there is no human interaction needed when deleting files which aids in compliance if your team uses more manual processes than automated ones (like automated backups).

An immutable store for SIEM data needs 2 things

a data retention policy mechanism that can prune old data while still providing cryptographic verification of the data that remains in the store. And a way to cryptographically export data for law enforcement analysis or other means. A simple data dump won’t do because once data is stored in a simple file or database it loses its cryptographic verification.

To ensure full tamperproof security, a data retention policy mechanism is needed that can prune old data while still providing cryptographic verification of the data that remains in the store. And a way to cryptographically export data for law enforcement analysis or other means. A simple data dump won’t do because once data is stored in a simple file or database it loses its cryptographic verification.

Immutable databases help cybersecurity teams provide proof of evidence in a court of network security events.

Immutable databases are tamperproof, meaning that they prevent unauthorized modification of the data stored within them. This can be extremely helpful in situations where you need to prove in court that your SIEM logs have not been tampered with.

For example, if a case goes to court and you want to demonstrate that a specific event occurred at a certain time, immutable databases ensure that there is no way for anyone else to change this information. This means that during an investigation, cybersecurity teams can prove evidence of network security events without fear of being accused of tampering with their own data.

Storing logs in an immutable database like immudb provide significant security, safety, and business benefits to your organization.

Immudb is a tamperproof database that provides cryptographic verification of data and audit trails. Immudb allows you to keep your SIEM logs in a tamperproof environment, which can help eliminate the risk of unauthorized modification by users or administrators. Immudb also provides a data retention policy mechanism that ensures that all logs remain intact for a specified period of time before being automatically deleted from the system. This allows you to ensure that only relevant information is retained for as long as needed while also ensuring compliance with legal requirements such as FINRA rules on holding stale data.

You can use immudb’s built-in functionality to cryptographically export your SIEM log files for law enforcement analysis via USB key or network share, effectively turning immudb into an immutable forensic evidence collection tool for security investigations involving sensitive information about bank account numbers, social security numbers, credit card details and more

Conclusion

Knowing how to analyze and respond to security incidents is key for any organization, but it’s even more important when it comes to protecting sensitive data like PHI. The ability of an immutable database like immudb provides significant business benefits including:

Use Case - Tamper-resistant Clinical Trials

Goal:

Blockchain PoCs were unsuccessful due to complexity and lack of developers.

Still the goal of data immutability as well as client verification is a crucial. Furthermore, the system needs to be easy to use and operate (allowing backup, maintenance windows aso.).

Implementation:

immudb is running in different datacenters across the globe. All clinical trial information is stored in immudb either as transactions or the pdf documents as a whole.

Having that single source of truth with versioned, timestamped, and cryptographically verifiable records, enables a whole new way of transparency and trust.

Use Case - Finance

Goal:

Store the source data, the decision and the rule base for financial support from governments timestamped, verifiable.

A very important functionality is the ability to compare the historic decision (based on the past rulebase) with the rulebase at a different date. Fully cryptographic verifiable Time Travel queries are required to be able to achieve that comparison.

Implementation:

While the source data, rulebase and the documented decision are stored in verifiable Blobs in immudb, the transaction is stored using the relational layer of immudb.

That allows the use of immudb’s time travel capabilities to retrieve verified historic data and recalculate with the most recent rulebase.

Use Case - eCommerce and NFT marketplace

Goal:

No matter if it’s an eCommerce platform or NFT marketplace, the goals are similar:

  • High amount of transactions (potentially millions a second)
  • Ability to read and write multiple records within one transaction
  • prevent overwrite or updates on transactions
  • comply with regulations (PCI, GDPR, …)


Implementation:

immudb is typically scaled out using Hyperscaler (i. e. AWS, Google Cloud, Microsoft Azure) distributed across the Globe. Auditors are also distributed to track the verification proof over time. Additionally, the shop or marketplace applications store immudb cryptographic state information. That high level of integrity and tamper-evidence while maintaining a very high transaction speed is key for companies to chose immudb.

Use Case - IoT Sensor Data

Goal:

IoT sensor data received by devices collecting environment data needs to be stored locally in a cryptographically verifiable manner until the data is transferred to a central datacenter. The data integrity needs to be verifiable at any given point in time and while in transit.

Implementation:

immudb runs embedded on the IoT device itself and is consistently audited by external probes. The data transfer to audit is minimal and works even with minimum bandwidth and unreliable connections.

Whenever the IoT devices are connected to a high bandwidth, the data transfer happens to a data center (large immudb deployment) and the source and destination date integrity is fully verified.

Use Case - DevOps Evidence

Goal:

CI/CD and application build logs need to be stored auditable and tamper-evident.
A very high Performance is required as the system should not slow down any build process.
Scalability is key as billions of artifacts are expected within the next years.
Next to a possibility of integrity validation, data needs to be retrievable by pipeline job id or digital asset checksum.

Implementation:

As part of the CI/CD audit functionality, data is stored within immudb using the Key/Value functionality. Key is either the CI/CD job id (i. e. Jenkins or GitLab) or the checksum of the resulting build or container image.

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