Added two playbooks

content/training/playbooks/_index.md

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+---
+menutitle: "Playbooks"
+title: "Playbooks"
+date: 2024-06-12T14:03:59Z
+draft: false
+weight: 150
+pre: <i class="fas fa-play"></i>
+no_edit: true
+disableToc: false
+no_children: true
+noDisqus: true
+outputs:
+- html
+- RSS
+---
+
+Velociraptor is an incredibly powerful tool, but sometimes it is hard
+to know where to start. This page aims to help newcomers to
+Velociraptor by presenting a set of playbooks to use when faced with
+certain tasks.
+
+{{% children description=True %}}

content/training/playbooks/preservation/_index.md

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+---
+title: "Preserving Forensic Evidence"
+description: |
+    A compromised endpoint is likely to be destroyed. You want to preserve raw files until you have an opportunity to analyse them later.
+
+tags:
+- preservation
+- acquisition
+---
+
+## Scenario
+
+As a system administrator you have a high level of confidence a
+certain endpoint is compromised. You wish to preserve critical
+evidence while arranging for a more experienced DFIR professional to
+examine the evidence.
+
+## Main takeaways
+
+1. This technique is a "shotgun" approach - it typically collects a
+   lot of data.
+2. Not very targeted.
+3. Does not scale to many endpoints - use when very confident an
+   endpoint is compromised.
+4. DFIR skill required - LOW.
+
+## Steps to take
+
+Some common artifacts that are used in a preservation collection:
+
+1. `Windows.KapeFiles.Targets` - collects files such as `$MFT`, log files etc.
+2. `Windows.Memory.Acquisition` - collects a physical memory image.
+
+### If Velociraptor is already installed on the endpoint
+
+For collecting from a single endpoint
+
+1. Search for the client you want to acquire from the main search screen.
+2. Select `Collected Artifacts` from the sidebar, then select `New
+   Collection` from the toolbar.
+3. For Windows systems, select `Windows.KapeFiles.Targets`.
+4. Select the `BasicCollection` or `Kape Triage` or `SANS Triage`
+   targets. These targets select the most common raw files used by
+   DFIR analysts.
+5. This artifact can collect a large amount of data, we recommend to
+   place resource limits to ensure that collection is not too
+   excessive.
+
+![Selecting the Windows.KapeFiles.Targets artifact](kape_targets.png)
+
+If you will have a number of endpoints to collect you can use a hunt
+to combine the data together:
+
+1. In the `Hunt Manager` screen, create a new hunt. Restrict the hunt
+   to a label `acquisition`.
+2. Proceed to collect the same artifacts as above
+3. As the investigation proceeds, when you find a client that warrants
+   a preservation collection, simply add a label `acquisition` to the
+   client. The `Windows.KapeFiles.Targets` will be automatically
+   scheduled on this client.
+4. You can view all acquired clients in the hunt overview page, and
+   create a large zip export of all preserved files.
+
+{{% notice warning "Ensure the hunt is restricted by labels!" %}}
+
+Make sure this hunt is restricted by labels! If it is not, it will be
+scheduled on all clients and may result in a lot of data being
+transferred to the server - this can result in the server's bandwidth
+being saturated, disk becoming full or server becoming unresponsive.
+
+If this happens you can stop the hunt in the GUI which will cancel all
+in-flight collections and eventually recover the server's bandwidth.
+
+{{% /notice %}}
+
+### If Velociraptor is not installed on the endpoint
+
+If Velociraptor is not already installed on the endpoint, you can use
+an `offline collector`. The Velociraptor `Offline Collector` is a
+preconfigured version of Velociraptor which can run on the endpoint
+and write all raw files into a ZIP archive.
+
+![Creating an offline collector](offline_collector.png)
+
+You can use a number of methods to push the offline to collection to
+the endpoint:
+
+1. Use an existing EDR or endpoint security product to run the binary
+   and retrieve the collected ZIP file.
+2. Use Group Policy to schedule a task that runs the collector from a
+   remote share.
+3. Use `WinRM` or `PsExec` to run the collector remotely (by careful
+   of pass the hash type attacks though).
+
+We recommend using the X509 encryption scheme to store the raw data to
+an encrypted container. This helps to protect it in transit.
+
+![Encrypting the collected data](encryoted_collector.png)
+
+You can also configure the offline collector to automatically upload
+the collection to a cloud storage, such as `S3`, `Google Cloud
+Storage` or a `Windows file share`.
+
+## When to use this technique?
+
+This technique should be used sparingly, usually targeting few
+systems, as it can transfer a large amount of data.
+
+Typically this technique is used when the endpoint is likely to be
+destroyed (e.g. re-imaged) or become inaccessible in the near
+future. The method is most suitable for preservation of raw data.
+
+## When not to use this technique?
+
+This workflow is not appropriate for triage. A triage workflow is
+about discovering unknown compromised endpoints and therefore by
+definition must be applied to a large number of endpoints. The
+`Preserving Forensic Evidence` workflow can not be applied to a large
+number of endpoints.
+
+The traditional digital forensics workflow consists of the following
+steps:
+
+1. `Acquisition` step collects a large amount of raw data to a central
+   server.
+2. `Analysis` step applies parsers and various dedicated tools in a
+   central "forensics workstation" on all the raw data collected.
+3. `Interpretation` step involves examining the output from the
+   various parsers to answer case specific questions.
+
+Many newcomers to Velociraptor have been trained with this workflow
+and try to apply it to Velociraptor.
+
+However this centralist approach to digital forensics does not scale
+in practice. When trying to apply this approach to a large network of
+endpoints, users are often overwhelmed with data (it is almost a right
+of passage for new Velociraptor users to completely fill their
+server's disk because they tried to collect all the log files from all
+the endpoints)
+
+Velociraptor's philosophy is different:
+
+1. Velociraptor considers the endpoint to be the ultimate source of truth.
+2. Therefore we rarely need to fetch the raw data from the endpoint!
+   Since Velociraptor can parse the raw data directly on the endpoint
+   we prefer asking case relevant questions from the entire network
+   directly.
+
+To explain this point, let's consider an example where we want to know
+if an executable file was recently downloaded onto the endpoint. We
+will attempt to parse the USN Journal to answer this question.
+
+The very traditional Digital Forensics process (i.e. back in the 90s)
+would require acquiring a bit for bit disk image of the suspected
+endpoint with a write blocker attached! Probably no-one does this any
+more!
+
+A more modern approach is to use a digital acquisition tool to copy
+just the `C:\$Extend\$UsnJrnl:$J` file in it's entirety for
+`Acquisition`, then apply a separate tool to parse the journal and
+search for any files written to the disk with a `.exe` extension.
+
+While this approach is better than acquiring the entire disk image
+(Average disks are of the range of 1-2Tb these days), it still
+requires collecting several hundred MB of data from each endpoint. If
+you have 10,000 endpoints this quickly becomes intractable.
+
+Velociraptor's approach is different: Since the endpoint is considered
+the source of truth, we just directly run our analysis on the
+endpoint. Collecting the `Windows.Forensics.Usn` artifact with a
+`FileNameRegex` filter of `.exe$` will query each machine to parse
+their own local copy of the USN journal to find all executables
+directly.
+
+We can collect this artifact using a hunt from the entire network at
+once. Since each endpoint will be doing the analysis in parallel,
+results will return in minutes regardless of how many endpoint there
+are!
+
+This is why we consider simple acquisition followed by central
+analysis workflows to be inferior to directly collecting the right
+artifacts.
+
+You should use the `Preserving Forensic Evidence` workflow only on
+systems that are known to have been compromised and you want to
+preserve the raw files for some reason.
+
+### Other considerations
+
+When collecting raw files from the endpoint we need to make a tradeoff:
+
+1. Collecting fewer files may miss some files that are needed later
+   during analysis.
+2. Collecting more files will result in smaller collection.
+
+Ultimately it is not possible to know in advance what type of evidence
+may be relevant. For example, we might collect the `$MFT` in our
+initial acquisition but subsequent analysis can show that certain
+files are critical (e.g. files in the user's `Downloads` directory).
+
+In a `Preserving Forensic Evidence` workflow we can not go back to the
+source of truth and check the files in the `Downloads` directory!
+
+Therefore it is always better to have Velociraptor already installed
+on the endpoint so we can pivot during the analysis phase and get
+additional information as required.

content/training/playbooks/triage-logs/_index.md

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+---
+title: "Triaging Logs"
+description: |
+    An endpoint is suspected of being compromised but you dont know
+    exactly what happened. You want to get an initial idea by examining
+    the logs on the actual endpoint.
+
+tags:
+- triage
+- preservation
+---
+
+## Scenario
+
+An endpoint is suspected of being compromised but you dont know
+exactly what happened. You want to get an initial idea by examining
+the logs on the actual endpoint.
+
+## Main takeaways
+
+1. This technique is similar to forwarding logs to a SIEM and applying
+   signatures.
+2. However we can choose very noisy signatures here
+3. We use stacking to quickly categorize the types of activity that
+   happens on the endpoint.
+
+## Steps to take
+
+Some common artifacts that are used for `Triaging Logs`
+
+1. `Windows.Hayabusa.Rules` should be imported using `Server.Import.CuratedSigma`
+2. `Exchange.Windows.EventLogs.Hayabusa` should be imported from the
+   artifact exchange.
+
+### Importing Windows.Hayabusa.Rules
+
+1. Select the `Server Artifacts` from the sidebar.
+2. Add a collection, search for `Server.Import.CuratedSigma` and
+   import the `Windows.Hayabusa.Rules`. This will import the latest
+   version of the artifact.
+
+This artifact uses the built in `Sigma Engine` in Velociraptor. The
+artifact packages the curated `Hayabusa` rules in a convenient
+artifact. Rules are categorized by `RuleLevel` and `RuleStatus` which
+generally try to balance how noisy a rule against its detection
+efficacy.
+
+![Sigma workflow in Velociraptor](velociraptor_sigma_flow.png)
+
+Because we are trying to triage the endpoint, we actually want to see
+all the hits, even if they are noisy. We will apply stacking later to
+quickly triage the type of activity on the endpoint. So in this case
+we should select to apply all the rules.
+
+![Applying all Sigma Rules](all_rules.png)
+
+Once the artifact is collected from the endpoint we can stack the hits
+in the GUI:
+
+1. Update the notebook to remove the `LIMIT 50`. This will select all
+   rows in one table. Typically there should be many thousands of
+   rows because we added all the noisy rules.
+2. Sort by the rule `Title`. Hover the mouse on the column header and
+   click the `Sort` button.
+3. Once the column is sorted, the stacking button should appear.
+
+![Stacking a column](stacking_a_column.png)
+
+4. Clicking the stacking button will show a summary of the different
+   rules matching and a count of how many times each rule made a hit.
+
+![Viewing column summaries](viewing_column_stack.png)
+
+5. Clicking on any of the rules navigates the table to the list of
+   rules that actually hit.
+
+![Viewing common rows](viewing_common_rows.png)
+
+Using this technique it is possible to quickly identify the types or
+categories of activity on the endpoint and see the most suspicious
+rules. Due to the stacking we dont need to review each individual hit,
+but only the different types of rules.
+
+For example, say we see a rule description a `PsExec` lateral
+movement, we can quickly identify if `PsExec` is expected for this
+environment, or does it represent a potential threat. If I identify
+the rule as important, I can then review each instance to get more
+information about what commands were run.
+
+## Using the Exchange.Windows.EventLogs.Hayabusa
+
+The `Exchange.Windows.EventLogs.Hayabusa` artifact is available in the
+artifact exchange. This artifact uses an external binary `Hayabusa` to
+evaluate the `Sigma` rules from the `Hayabusa` project.
+
+Post processing and analysing the results from this artifact is
+similar to the procedure described above.
+
+
+## Discussion and limitations
+
+This technique is similar to many SIEMs which forward event logs from
+the endpoint and apply matching rules. There are some fundamental
+differences though:
+
+1. SIEMs typically only forward a small subset of logs since the more
+   logs are collected the more data the SIEM backend needs to
+   handle. Typically SIEMs forward logs such as `Sysmon Process
+   Execution` but do not forward other logs for example `BITS Client
+   Operational Logs`.
+
+2. SIEM rules are also written to ensure they have a low false
+   positive rate. This means that suspicious activity in one
+   environment which is common in another setting, might not trigger a
+   detection. By stacking on all noisy rules we get to decide for
+   ourselves if a particular rule is acceptable for this environment.
+
+   For example an administrator RDP login may be perfectly normal in
+   some environments but a red flag in others!  SIEM detections are
+   rarely tuned to the environment.
+
+3. A SIEM may not be present or well tuned, in a particular
+   environment. Running the `Sigma` log triaging workflow can
+   compensate for the lack of a SIEM.
+
+4. Data retention is different from a SIEM. Typically SIEMs only
+   maintain logs for limited time (sometimes as low as a month). On
+   the other hand log files are typically rotated based on size. This
+   means that sometimes logs will be present on the endpoint for
+   longer than in the SIEM, while other times the SIEM will contain
+   logs that were already rotate on the endpoint.
+
+5. Because this technique relies on locally stored logs, it is
+   susceptible to logs being cleared by attackers.
+
+## Real time monitoring
+
+As an additional step you can enable the `Windows.Hayabusa.Monitoring`
+artifact for real time detection of the same `Sigma` rules. This can
+provide coverage for any future compromises