diff --git a/backend/app/services/memory/procedural/memory.py b/backend/app/services/memory/procedural/memory.py
index dca4eeb..997fdd5 100644
--- a/backend/app/services/memory/procedural/memory.py
+++ b/backend/app/services/memory/procedural/memory.py
@@ -22,6 +22,25 @@ from app.services.memory.types import Procedure, ProcedureCreate, RetrievalResul
 logger = logging.getLogger(__name__)
 
 
+def _escape_like_pattern(pattern: str) -> str:
+    """
+    Escape SQL LIKE/ILIKE special characters to prevent pattern injection.
+
+    Characters escaped:
+    - % (matches zero or more characters)
+    - _ (matches exactly one character)
+    - \\ (escape character itself)
+
+    Args:
+        pattern: Raw search pattern from user input
+
+    Returns:
+        Escaped pattern safe for use in LIKE/ILIKE queries
+    """
+    # Escape backslash first, then the wildcards
+    return pattern.replace("\\", "\\\\").replace("%", "\\%").replace("_", "\\_")
+
+
 def _model_to_procedure(model: ProcedureModel) -> Procedure:
     """Convert SQLAlchemy model to Procedure dataclass."""
     return Procedure(
@@ -320,7 +339,9 @@ class ProceduralMemory:
         if search_terms:
             conditions = []
             for term in search_terms:
-                term_pattern = f"%{term}%"
+                # Escape SQL wildcards to prevent pattern injection
+                escaped_term = _escape_like_pattern(term)
+                term_pattern = f"%{escaped_term}%"
                 conditions.append(
                     or_(
                         ProcedureModel.trigger_pattern.ilike(term_pattern),
@@ -368,6 +389,10 @@ class ProceduralMemory:
         Returns:
             Best matching procedure or None
         """
+        # Escape SQL wildcards to prevent pattern injection
+        escaped_task_type = _escape_like_pattern(task_type)
+        task_type_pattern = f"%{escaped_task_type}%"
+
         # Build query for procedures matching task type
         stmt = (
             select(ProcedureModel)
@@ -376,8 +401,8 @@ class ProceduralMemory:
                     (ProcedureModel.success_count + ProcedureModel.failure_count)
                     >= min_uses,
                     or_(
-                        ProcedureModel.trigger_pattern.ilike(f"%{task_type}%"),
-                        ProcedureModel.name.ilike(f"%{task_type}%"),
+                        ProcedureModel.trigger_pattern.ilike(task_type_pattern),
+                        ProcedureModel.name.ilike(task_type_pattern),
                     ),
                 )
             )
diff --git a/backend/app/services/memory/semantic/memory.py b/backend/app/services/memory/semantic/memory.py
index bca103b..2dde3d0 100644
--- a/backend/app/services/memory/semantic/memory.py
+++ b/backend/app/services/memory/semantic/memory.py
@@ -22,6 +22,25 @@ from app.services.memory.types import Episode, Fact, FactCreate, RetrievalResult
 logger = logging.getLogger(__name__)
 
 
+def _escape_like_pattern(pattern: str) -> str:
+    """
+    Escape SQL LIKE/ILIKE special characters to prevent pattern injection.
+
+    Characters escaped:
+    - % (matches zero or more characters)
+    - _ (matches exactly one character)
+    - \\ (escape character itself)
+
+    Args:
+        pattern: Raw search pattern from user input
+
+    Returns:
+        Escaped pattern safe for use in LIKE/ILIKE queries
+    """
+    # Escape backslash first, then the wildcards
+    return pattern.replace("\\", "\\\\").replace("%", "\\%").replace("_", "\\_")
+
+
 def _model_to_fact(model: FactModel) -> Fact:
     """Convert SQLAlchemy model to Fact dataclass."""
     # SQLAlchemy Column types are inferred as Column[T] by mypy, but at runtime
@@ -251,7 +270,9 @@ class SemanticMemory:
         if search_terms:
             conditions = []
             for term in search_terms[:5]:  # Limit to 5 terms
-                term_pattern = f"%{term}%"
+                # Escape SQL wildcards to prevent pattern injection
+                escaped_term = _escape_like_pattern(term)
+                term_pattern = f"%{escaped_term}%"
                 conditions.append(
                     or_(
                         FactModel.subject.ilike(term_pattern),
@@ -295,12 +316,16 @@ class SemanticMemory:
         """
         start_time = time.perf_counter()
 
+        # Escape SQL wildcards to prevent pattern injection
+        escaped_entity = _escape_like_pattern(entity)
+        entity_pattern = f"%{escaped_entity}%"
+
         stmt = (
             select(FactModel)
             .where(
                 or_(
-                    FactModel.subject.ilike(f"%{entity}%"),
-                    FactModel.object.ilike(f"%{entity}%"),
+                    FactModel.subject.ilike(entity_pattern),
+                    FactModel.object.ilike(entity_pattern),
                 )
             )
             .order_by(desc(FactModel.confidence), desc(FactModel.last_reinforced))