BloodHound needs to be fed JSON files containing info on the objects and relationships within the AD domain. This information are obtained with collectors (also called ingestors). The best way of doing this is using the official SharpHound (C#) collector.
It must be run from the context of a domain user, either directly through a logon or through another method such as runas (
runas /netonly /user:$DOMAIN\$USER) (see Impersonation). Alternatively, SharpHound can be used with the
LdapPasswordflags for that matter.
SharpHound.exe --collectionmethods All
The previous commands are basic but some options (i.e. Stealth and Loop) can be very useful depending on the context
# Perform stealth collection methods
SharpHound.exe --collectionmethods All --Stealth
# Loop collections (especially useful for session collection)
# e.g. collect sessions every 10 minutes for 3 hours
SharpHound.exe --collectionmethods Session --Loop --loopduration 03:00:00 --loopinterval 00:10:00
# Use LDAPS instead of plaintext LDAP
From UNIX-like system, a non-official (but very effective nonetheless) Python version can be used.
bloodhound.py --zip -c All -d $DOMAIN -u $USERNAME -p $PASSWORD -dc $DOMAIN_CONTROLLER
Once the collection is over, the data can be uploaded and analysed in BloodHound by doing the following.
- Find paths between specified nodes
- Run pre-built analytics queries to find common attack paths
- Run custom queries to help in finding more complex attack paths or interesting objects
- Run manual neo4j queries
- Mark nodes as high value targets for easier path finding
- Mark nodes as owned for easier path finding
- Find information about selected nodes: sessions, properties, group membership/members, local admin rights, Kerberos delegations, RDP rights, outbound/inbound control rights (ACEs), and so on
- Find help about edges/attacks (abuse, opsec considerations, references)